{"id":508112,"date":"2018-10-24T18:05:11","date_gmt":"2018-10-25T01:05:11","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-event&p=508112"},"modified":"2025-08-06T11:56:45","modified_gmt":"2025-08-06T18:56:45","slug":"neurips-2018","status":"publish","type":"msr-event","link":"https:\/\/www.microsoft.com\/en-us\/research\/event\/neurips-2018\/","title":{"rendered":"Microsoft @ NeurIPS 2018"},"content":{"rendered":"\n\n

Venue:<\/strong> Palais des Congr\u00e8s de Montr\u00e9al (opens in new tab)<\/span><\/a>
\n1H5 Place Jean-Paul-Riopelle
\nMontr\u00e9al, Qu\u00e9bec H2Z 1H5
\nCanada<\/p>\n

Website:<\/strong> NeurIPS 2018 (opens in new tab)<\/span><\/a>Opens in a new tab<\/span><\/p>\n

Microsoft is excited to be a Diamond sponsor of the 32nd annual conference on Neural Information Processing Systems (opens in new tab)<\/span><\/a>. Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities (opens in new tab)<\/span><\/a> with Microsoft.<\/p>\n

Program Chair<\/h2>\n

Hanna Wallach<\/a><\/p>\n

\n

Tutorial Chair<\/h2>\n<\/div>\n
\n

Jenn Wortman Vaughan<\/a><\/p>\n<\/div>\n

Workshop Organizers<\/h2>\n

Prateek Jain<\/a> | 2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2) (opens in new tab)<\/span><\/a><\/p>\n

Abhishek Gupta | AI for social good (opens in new tab)<\/span><\/a><\/p>\n

Evelyne Viegas<\/a> | CiML 2018 – Machine Learning competitions “in the wild”: Playing in the real world or in real time (opens in new tab)<\/span><\/a><\/p>\n

Rich Caruana<\/a> | Critiquing and Correcting Trends in Machine Learning (opens in new tab)<\/span><\/a><\/p>\n

Tristan Naumann<\/a> | Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare (opens in new tab)<\/span><\/a><\/p>\n

Siddhartha Sen<\/a> | MLSys: Workshop on Systems for ML and Open Source Software (opens in new tab)<\/span><\/a><\/p>\n

Olya Ohrimenko<\/a> | Privacy Preserving Machine Learning (opens in new tab)<\/span><\/a><\/p>\n

Marc-Alexandre C\u00f4t\u00e9<\/a>, Wendy Tay<\/a>, Adam Trischler<\/a>, Hal Daum\u00e9 III<\/a>, Nate Kushman<\/a>, Alessandro Sordoni<\/a> | Wordplay: Reinforcement and Language Learning in Text-based Games (opens in new tab)<\/span><\/a><\/p>\n

Volunteer Workflow Team<\/h2>\n

Chinmay Singh<\/a>Opens in a new tab<\/span><\/p>\n

\n

Tuesday, December 4, 2018<\/h2>\n
\n

Adversarial Multiple Source Domain Adaptation (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #107<\/h3>\n

Han Zhao, Shanghang Zhang, Guanhang Wu, Jose M. F. Moura, Joao P. Costeira, Geoffrey Gordon<\/a><\/p>\n

FRAGE: Frequency-Agnostic Word Representation<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #153<\/h3>\n

Chengyue Gong, Di He<\/a>, Xu Tan<\/a>, Tao Qin<\/a>, Liwei Wang, Tie-Yan Liu<\/a><\/p>\n

Frequency-Domain Dynamic Pruning for Convolutional Neural Networks (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #67<\/h3>\n

Zhenhua Liu, Jizheng Xu, Xiulian Peng<\/a>, Ruiqin Xiong<\/p>\n

Heterogeneous Bitwidth Binarization in Convolutional Neural Networks<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #69<\/h3>\n

Josh Fromm, Shwetak Patel, Matthai Philipose<\/a><\/p>\n

Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\n

Don Dennis, Chirag Pabbaraju<\/strong>, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a><\/p>\n

Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #73<\/h3>\n

Minjia Zhang<\/a>, Xiaodong Liu<\/a>, Wenhan Wang<\/strong>, Jianfeng Gao<\/a>, Yuxiong He<\/a><\/p>\n

On the Dimensionality of Word Embedding (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #110<\/h3>\n

Zi Yin, Yuanyuan Shen<\/strong><\/p>\n

The Lingering of Gradients: How to Reuse Gradients Over Time (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #2<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/p>\n

Towards Text Generation with Adversarially Learned Neural Outlines (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #14<\/h3>\n

Sandeep Subramanian, Sai Rajeswar Mudumba, Adam Trischler<\/a>, Alessandro Sordoni<\/a>, Aaron Courville, Chris Pal<\/p>\n

A Dual Framework for Low-rank Tensor Completion (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #146<\/h3>\n

Madhav Nimishakavi, Bamdev Mishra (opens in new tab)<\/span><\/a>, Pratik Kumar Jawanpuria<\/strong> (opens in new tab)<\/span><\/a><\/p>\n

Bounded-Loss Private Prediction Markets (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #28<\/h3>\n

Rafael Frongillo, Bo Waggoner<\/strong><\/p>\n

Contamination Attacks in Multi-Party Machine Learning (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #158<\/h3>\n

Jamie Hayes, Olya Ohrimenko<\/a><\/p>\n

Dialog-based Interactive Image Retrieval<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #55<\/h3>\n

Xiaoxiao Guo, Hui Wu, Yu Cheng<\/strong>, Steven Rennie, Rogerio Schmidt Feris<\/p>\n

Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #93<\/h3>\n

Daya Guo, Duyu Tang<\/a>, Nan Duan<\/a>, Ming Zhou<\/a>, Jian Yin<\/p>\n

Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #94<\/h3>\n

Yizhe Zhang<\/a>, Michel Galley<\/a>, Jianfeng Gao<\/a>, Zhe Gan<\/strong>, Xiujun Li<\/a>, Chris Brockett<\/a>, Bill Dolan<\/a><\/p>\n

Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #85<\/h3>\n

Tianyu He, Tao Qin<\/a>, Tie-Yan Liu<\/a>, Yingce Xia<\/strong>, Xu Tan<\/a>, Di He<\/a>, Zhibo Chen<\/p>\n

Local Differential Privacy for Evolving Data (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\n

Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/strong><\/p>\n

Precision and Recall for Time Series (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #116<\/h3>\n

Nesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich<\/p>\n

Supervising Unsupervised Learning<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #164<\/h3>\n

Vikas Garg, Adam Kalai<\/a><\/p>\n

Turbo Learning for Captionbot and Drawingbot<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #54<\/h3>\n

Qiuyuan Huang<\/a>, Pengchuan Zhang<\/a>, Oliver Wu, Lei Zhang<\/a><\/p>\n

\n

Wednesday, December 5, 2018<\/h2>\n
\n

Adversarial Text Generation via Feature-Mover’s Distance<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #129<\/h3>\n

Liqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan<\/strong>, Haichao Zhang, Yizhe Zhang<\/a>, Lawrence Carin<\/p>\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #159<\/h3>\n

Sampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/strong>, Zhiwei Steven Wu<\/p>\n

Constructing Unrestricted Adversarial Examples with Generative Models (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #149<\/h3>\n

Yang Song, Rui Shu, Nate Kushman<\/a>, Stefano Ermon<\/p>\n

Global Non-convex Optimization with Discretized Diffusions (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #18<\/h3>\n

Murat A. Erdogdu, Lester Mackey<\/a>, Ohad Shamir<\/p>\n

Inexact trust-region algorithms on Riemannian manifolds (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #15<\/h3>\n

Hiroyuki Kasai, Bamdev Mishra<\/strong><\/p>\n

Is Q-Learning Provably Efficient? (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\n

Chi Jin, Zeyuan Allen-Zhu<\/a>, Sebastien Bubeck<\/a>, Michael Jordon<\/p>\n

M-Walk: Learning to Walk over Graphs with Monte Carlo Tree Search<\/a>
\n10:45 AM-12:45 PM | Room 210&230 | AB #164<\/h3>\n

Yelong Shen<\/strong>, Jianshu Chen, Po-Sen Huang, Yuqing Guo<\/strong>, Jianfeng Gao<\/a><\/p>\n

On Oracle-Efficient PAC RL with Rich Observations<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #111<\/h3>\n

Christoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a><\/p>\n

On the Local Hessian in Back-propagation<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #43<\/h3>\n

Huishuai Zhang<\/a>, Wei Chen<\/a>, Tie-Yan Liu<\/a><\/p>\n

Recurrent Transformer Networks for Semantic Correspondence (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #119<\/h3>\n

Seungryong Kim, Stephen Lin<\/strong>, SANG RYUL JEON, Dongbo Min, Kwanghoon Sohn<\/p>\n

Universal Growth in Production Economies<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\n

Simina Branzei, Ruta Mehta, Noam Nisan<\/strong><\/p>\n

Weakly Supervised Dense Event Captioning in Videos (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #125<\/h3>\n

Xuguang Duan, Wenbing Huang, Chuang Gan, Jingdong Wang<\/a>, Wenwu Zhu, Junzhou Huang<\/p>\n

Natasha 2: Faster Non-Convex Optimization Than SGD<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #50<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/p>\n

Coupled Variational Bayes via Optimization Embedding (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #11<\/h3>\n

Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao<\/a>, Le Song<\/p>\n

Dual Policy Iteration<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #124<\/h3>\n

Wen Sun, Geoffrey Gordon<\/a>, Wen Sun, J. Andrew Bagnell<\/p>\n

Probabilistic Matrix Factorization for Automated Machine Learning (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\n

Nicolo Fusi<\/a>, Rishit Sheth<\/a>, Melih Elibol<\/strong><\/p>\n

NEON2: Finding Local Minima via First-Order Oracles (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #45<\/h3>\n

Zeyuan Allen-Zhu<\/a>, Yuanzhi Li<\/p>\n

Teaching Inverse Reinforcement Learners via Features and Demonstrations (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #167<\/h3>\n

Luis Haug, Sebastian Tschiatschek<\/a>, Adish Singla<\/p>\n

\n

Thursday, December 6, 2018<\/h2>\n
\n

Contextual bandits with surrogate losses: Margin bounds and efficient algorithms<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\n

Dylan Foster, Akshay Krishnamurthy<\/a><\/p>\n

FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network<\/a>
\n10:45 AM – 12:45 PM | Room 210&230 AB #89<\/h3>\n

Aditya Kusupati<\/strong>, Manish Singh,\u00a0Kush Bhatia, Ashish Kumar, \u00a0 Prateek Jain<\/a>, Manik Varma<\/a><\/p>\n

Gaussian Process Prior Variational Autoencoders (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #63<\/h3>\n

Nicolo Fusi<\/a>, Luca Saglietti<\/strong>, Francesco Paolo Casale<\/a>, Adrian Dalca, Jennifer Listgarten<\/p>\n

Learning to Teach with Dynamic Loss Functions (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #155<\/h3>\n

Tao Qin<\/a>, Tie-Yan Liu<\/a>, Fei Tian<\/a>, Yingce Xia<\/strong>, Lijun Wu, Yingce Xia, Lai Jian-Huang<\/p>\n

Byzantine Stochastic Gradient Descent (opens in new tab)<\/span><\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #164<\/h3>\n

Dan Alistarh, Zeyuan Allen-Zhu<\/a>, Jerry Li<\/p>\n

Towards Deep Conversational Recommendations<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #118<\/h3>\n

Raymond Li, Samira Ebrahimi Kahou<\/a>, Hannes Schulz<\/a>,Vincent Michalski, Laurent Charlin, Chris Pal<\/p>\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\n

Kevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Yin Tat Lee, Laurent Massoulie<\/p>\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #63<\/h3>\n

Raghav Somani<\/strong>, Chirag Gupta, Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/p>\n

Community Exploration: From Offline Optimization to Online Learning (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\n

Xiaowei Chen, Weiran Huang, Wei Chen<\/a>, John C.S. Lui<\/p>\n

Constrained Graph Variational Autoencoders for Molecule Design<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #103<\/h3>\n

Qi Liu, Miltos Allamanis<\/a>, Marc Brockschmidt<\/a>, Alexander Gaunt<\/a><\/p>\n

How To Make the Gradients Small Stochastically (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #74<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/p>\n

Learning Beam Search Policies via Imitation Learning (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB#104<\/h3>\n

Renato Negrinho, Matthew Gormley, Geoffrey Gordon<\/a><\/p>\n

Learning SMaLL Predictors<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #98<\/h3>\n

Vikas K. Garg, Ofer Dekel<\/a>, Lin Xiao<\/a><\/p>\n

Neural Architecture Optimization<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #123<\/h3>\n

Renqian Luo, Fei Tian<\/a>, Tao Qin<\/a>, Enhon Chen, Tie-Yan Liu<\/a><\/p>\n

Random Feature Stein Discrepancies (opens in new tab)<\/span><\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #78<\/h3>\n

Jonathan Huggins, Lester Mackey<\/a><\/p>\n

\n

Opens in a new tab<\/span><\/p>\n

Local Differential Privacy for Evolving Data
\nTuesday, December 4, 2018 | 3:35 PM\u20133:40 PM | Room 517CD<\/h3>\n

Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/a><\/strong><\/p>\n

Bounded-Loss Private Prediction Markets
\nTuesday, December 4, 2018 | 4:05 PM\u20134:10 PM | Room 517CD<\/h3>\n

Rafael Frongillo, Bo Waggoner<\/a><\/strong><\/p>\n

Precision and Recall for Time Series
\nTuesday, December 4, 2018 | 4:50 PM\u20134:55 PM | Room 220CD<\/h3>\n

Nesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich<\/p>\n

Supervising Unsupervised Learning
\nTuesday, December 4, 2018 | 4:55 PM\u20135:00 PM | Room 517CD<\/h3>\n

Vikas Garg, Adam Kalai<\/a><\/strong><\/p>\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
\nWednesday, December 5, 2018 | 9:45 AM\u20139:50 AM | Room 220CD<\/h3>\n

Sampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/a><\/strong>, Zhiwei Steven Wu<\/p>\n

Recurrent Transformer Networks for Semantic Correspondence
\nWednesday, December 5, 2018 | 10:20 AM\u201310:25 AM | Room 220E<\/h3>\n

Seungryong Kim, Stephen Lin<\/a><\/strong>, Sang Ryul Jeon, Dongbo Min, Kwanghoon Sohn<\/p>\n

On Oracle-Efficient PAC RL with Rich Observations
\nWednesday, December 5, 2018 | 10:25 AM\u201310:30 AM | Room 220CD<\/h3>\n

Christoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a><\/strong><\/p>\n

Natasha 2: Faster Non-Convex Optimization Than SGD
\nWednesday, December 5, 2018 | 4:40 PM\u20134:45 PM | Room 517CD<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/strong><\/p>\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds
\nThursday, December 6, 2018 | 4:55 PM\u20135:00 PM | Room 220CD<\/h3>\n

Raghav Somani,<\/strong> Chirag Gupta,<\/strong> Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/strong>Opens in a new tab<\/span><\/p>\n

On the Dimensionality of Word Embedding
\nThursday, December 6, 2018 | 10:05AM \u2013 10:20AM | Room 220E<\/h3>\n

Zi Yin, Yuanyuan Shen<\/strong><\/p>\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>
\nThursday, December 6, 2018 | 3:50 PM\u20134:05 PM | Room 517CD<\/h3>\n

Kevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Laurent Massouli\u00e9, Yin Tat LeeOpens in a new tab<\/span><\/p>\n

2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2) (opens in new tab)<\/span><\/a>
\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Invited speaker: Manik Varma<\/a><\/p>\n

MLSys: Workshop on Systems for ML and Open Source Software (opens in new tab)<\/span><\/a>
\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Accepted paper: Matteo Interlandi,\u00a0Sergiy Matusevych,\u00a0Saeed Amizadeh, Shauheen Zahirazami, Markus Weimer<\/strong> | Machine Learning at Microsoft with ML.NET<\/p>\n

Accepted paper:\u00a0Gyeong-In Yu,\u00a0Saeed Amizadeh<\/b>,\u00a0Byung-Gon Chun, Markus Weimer, Matteo Interlandi<\/b> | Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach<\/p>\n

Accepted paper: Yaoqing Yang, Matteo Interlandi<\/b>, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer<\/b> | Coded Elastic Computing<\/p>\n

2nd Conversational AI: \u201cToday’s Practice and Tomorrow’s Potential\u201d (opens in new tab)<\/span><\/a>
\nFriday, December 7, 2018 | 9:00 AM-5:30 PM<\/h3>\n

Accepted paper: Elnaz Nouri<\/a>, Ehsan Hosseini-Asl | Toward Scalable Neural Dialogue State Tracking Model<\/p>\n

Workshop on Security in Machine Learning (opens in new tab)<\/span><\/a>
\nFriday, December 7, 2018 | 11:00 AM-1:30 PM<\/h3>\n

Keynote: danah boyd<\/a><\/p>\n

Interpretability and Robustness in Audio, Speech, and Language (opens in new tab)<\/span><\/a>
\nSaturday, December 8, 2018 | 9:00 AM-9:30 AM<\/h3>\n

Invited Speaker 1: Rich Caruana<\/a><\/p>\n

Relational Representation Learning (opens in new tab)<\/span><\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

10:15 AM spotlight talk: Saeed Amizadeh |<\/strong> A Neural Framework for Learning DAG to DAG Translation
\n<\/strong><\/p>\n

Privacy Preserving Machine Learning (opens in new tab)<\/span><\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Poster: Bolin Ding, Janardhan Kulkarni and Sergey Yekhanin<\/strong> | A Distributed Algorithm For Differentially Private Heavy Hitters (opens in new tab)<\/span><\/a><\/p>\n

Poster: Joshua Allen, <\/strong>Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olya Ohrimenko and Sergey Yekhanin<\/strong> | An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors (opens in new tab)<\/span><\/a><\/p>\n

Second Workshop on Machine Learning for Creativity and Design (opens in new tab)<\/span><\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Poster: Khyatti Gupta, Sonam Damani, Kedhar Nath Narahari | <\/strong>Using AI to Design Stone Jewelry<\/p>\n

Wordplay: Reinforcement and Language Learning in Text-based Games (opens in new tab)<\/span><\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Invited speaker: Katja Hofmann<\/strong><\/p>\n

Machine Learning Open Source Software 2018: Sustainable communities (opens in new tab)<\/span><\/a>
\nSaturday, December 8, 2018 | 8:30 AM-5:35 PM<\/h3>\n

11:00AM poster: Mayank Meghwankshi<\/strong>, Pratik Jawanpuria<\/strong>, Anoop Kunchukuttan<\/strong>, Hiroyuki Kasai, Bamdev Michra<\/strong>, McTorch | a manifold optimization library for deep learning<\/p>\n

11:00AM poster: Markus Weimer<\/a> | Machine Learning at Microsoft with ML.NETOpens in a new tab<\/span><\/p>\n

Booth Demos<\/h2>\n

Come by our booth (#203) to see demos of our latest research. See schedule below:<\/p>\n

<\/div>\n

Sunday, December 2<\/h3>\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
10:00 AM\u201310:30 AM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:30 PM\u20131:15 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:15 PM\u20132:00 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
4:00 PM\u20134:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
6:30 PM\u20137:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Monday, December 3<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
10:30 AM\u201311:00 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:00 PM\u20131:45 PM<\/td>\nMulti-Word Imput<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:45 PM\u20132:30 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
4:30 PM\u20135:00 PM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
6:30 PM\u20137:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
7:30 PM\u20138:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Tuesday, December 4<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
9:40 AM\u201310:05 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:15 PM<\/td>\nMulti-Word Imput<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:05 PM\u20133:30 PM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Wednesday, December 5<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
9:20 AM\u20139:45 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:15 PM<\/td>\nTextWorld<\/td>\n<\/tr>\n
<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:05 PM\u20133:30 PM<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Thursday, December 6<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
9:20 AM\u20139:45 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nMulti-Word Imput<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:15 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:05 PM\u20133:30 PM<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Friday, December 7<\/h3>\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
10:30 AM\u201311:00 AM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:00 PM\u201312:45 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:00 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:00 PM\u20133:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Conference Demo Sessions<\/h2>\n

ML on Resource Constrained Edge Devices \u2013 GesturePod! (opens in new tab)<\/span><\/a>
\nSunday, December 2, 2018 | 2:00 PM\u20136:30 PM | Room 510ABCD<\/h3>\n

Shishir G. Patil, Don Kurian Dennis, Harsha Vardhan Simhadri, Prateek Jain (opens in new tab)<\/span><\/a>
\n<\/strong><\/p>\n

Ruuh: A Deep Learning Based Conversational Social Agent (opens in new tab)<\/span><\/a>
\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D3<\/h3>\n

Manoj Chinnakotla, Kedhar Narahari, Nitya Raviprakash, Umang Gupta, Ankush Chatterjee, Sneha Magapu, Sonam Damani, Abhishek Mathur, Puneet Agrawal, Meghana Joshi, Khyatti Gupta<\/strong><\/p>\n

TextWorld: A Learning Environment for Text-based Games (opens in new tab)<\/span><\/a>
\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D10<\/h3>\n

Eric Yuan (opens in new tab)<\/span><\/a>, Wendy Tay (opens in new tab)<\/span><\/a>, Marc-Alexandre C\u00f4t\u00e9 (opens in new tab)<\/span><\/a><\/p>\n

Multi-Word Imputation and Sentence Expansion (opens in new tab)<\/span><\/a>
\nWednesday, December 5, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D7<\/h3>\n

Douglas Orr, Osman Ramadan, <\/strong>Dmitry Stratiychuk, B\u0142a\u017cej Czapp<\/strong>Opens in a new tab<\/span><\/p>\n

\t\t\t

\n\t\t\t
\n\t\t\t\t\n
\n\t
\n\t\t

\n\t\t\t\t\t\t\t NeurIPS Conference Analytics<\/a>\n\t\t\t\t\t<\/h3>\n\n\t\t
\n\t\t\t
\n\t\t\t\t\t\t\t\tMicrosoft Academic | November 23, 2018

<\/h3>

The Microsoft Academic Graph makes it possible to gain analytic insights about any of the entities within it: publications, authors, institutions, topics, journals, and conferences.\t\t\t<\/div>\n\t\t<\/div>\n\n\t<\/div>\n<\/article>\n<\/p>\t\t\t<\/div>\n\t\t<\/div>\n\t\tOpens in a new tab<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft is excited to be a Diamond sponsor of the thirty-second annual conference on Neural Information Processing Systems (NIPS). Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops at NIPS. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities with Microsoft.<\/p>\n","protected":false},"featured_media":508535,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_startdate":"2018-12-02","msr_enddate":"2018-12-08","msr_location":"Montreal, Quebec, Canada","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"https:\/\/nips.cc\/Register\/view-registration","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":false,"msr_private_event":false,"msr_hide_image_in_river":0,"footnotes":""},"research-area":[13556],"msr-region":[197900],"msr-event-type":[197941],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-508112","msr-event","type-msr-event","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-region-north-america","msr-event-type-conferences","msr-locale-en_us"],"msr_about":"\n\n

Venue:<\/strong> Palais des Congr\u00e8s de Montr\u00e9al (opens in new tab)<\/span><\/a>
\n1H5 Place Jean-Paul-Riopelle
\nMontr\u00e9al, Qu\u00e9bec H2Z 1H5
\nCanada<\/p>\n

Website:<\/strong> NeurIPS 2018 (opens in new tab)<\/span><\/a>Opens in a new tab<\/span><\/p>\n

Microsoft is excited to be a Diamond sponsor of the 32nd annual conference on Neural Information Processing Systems<\/a>. Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities<\/a> with Microsoft.<\/p>\n

Program Chair<\/h2>\n

Hanna Wallach<\/a><\/p>\n

\n

Tutorial Chair<\/h2>\n<\/div>\n
\n

Jenn Wortman Vaughan<\/a><\/p>\n<\/div>\n

Workshop Organizers<\/h2>\n

Prateek Jain<\/a> | 2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)<\/a><\/p>\n

Abhishek Gupta | AI for social good<\/a><\/p>\n

Evelyne Viegas<\/a> | CiML 2018 – Machine Learning competitions “in the wild”: Playing in the real world or in real time<\/a><\/p>\n

Rich Caruana<\/a> | Critiquing and Correcting Trends in Machine Learning<\/a><\/p>\n

Tristan Naumann<\/a> | Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare<\/a><\/p>\n

Siddhartha Sen<\/a> | MLSys: Workshop on Systems for ML and Open Source Software<\/a><\/p>\n

Olya Ohrimenko<\/a> | Privacy Preserving Machine Learning<\/a><\/p>\n

Marc-Alexandre C\u00f4t\u00e9<\/a>, Wendy Tay<\/a>, Adam Trischler<\/a>, Hal Daum\u00e9 III<\/a>, Nate Kushman<\/a>, Alessandro Sordoni<\/a> | Wordplay: Reinforcement and Language Learning in Text-based Games<\/a><\/p>\n

Volunteer Workflow Team<\/h2>\n

Chinmay Singh<\/a>Opens in a new tab<\/span><\/p>\n

\n

Tuesday, December 4, 2018<\/h2>\n
\n

Adversarial Multiple Source Domain Adaptation<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #107<\/h3>\n

Han Zhao, Shanghang Zhang, Guanhang Wu, Jose M. F. Moura, Joao P. Costeira, Geoffrey Gordon<\/a><\/p>\n

FRAGE: Frequency-Agnostic Word Representation<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #153<\/h3>\n

Chengyue Gong, Di He<\/a>, Xu Tan<\/a>, Tao Qin<\/a>, Liwei Wang, Tie-Yan Liu<\/a><\/p>\n

Frequency-Domain Dynamic Pruning for Convolutional Neural Networks<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #67<\/h3>\n

Zhenhua Liu, Jizheng Xu, Xiulian Peng<\/a>, Ruiqin Xiong<\/p>\n

Heterogeneous Bitwidth Binarization in Convolutional Neural Networks<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #69<\/h3>\n

Josh Fromm, Shwetak Patel, Matthai Philipose<\/a><\/p>\n

Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\n

Don Dennis, Chirag Pabbaraju<\/strong>, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a><\/p>\n

Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #73<\/h3>\n

Minjia Zhang<\/a>, Xiaodong Liu<\/a>, Wenhan Wang<\/strong>, Jianfeng Gao<\/a>, Yuxiong He<\/a><\/p>\n

On the Dimensionality of Word Embedding<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #110<\/h3>\n

Zi Yin, Yuanyuan Shen<\/strong><\/p>\n

The Lingering of Gradients: How to Reuse Gradients Over Time<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #2<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/p>\n

Towards Text Generation with Adversarially Learned Neural Outlines<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #14<\/h3>\n

Sandeep Subramanian, Sai Rajeswar Mudumba, Adam Trischler<\/a>, Alessandro Sordoni<\/a>, Aaron Courville, Chris Pal<\/p>\n

A Dual Framework for Low-rank Tensor Completion<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #146<\/h3>\n

Madhav Nimishakavi, Bamdev Mishra<\/a>, Pratik Kumar Jawanpuria<\/strong><\/a><\/p>\n

Bounded-Loss Private Prediction Markets<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #28<\/h3>\n

Rafael Frongillo, Bo Waggoner<\/strong><\/p>\n

Contamination Attacks in Multi-Party Machine Learning<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #158<\/h3>\n

Jamie Hayes, Olya Ohrimenko<\/a><\/p>\n

Dialog-based Interactive Image Retrieval<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #55<\/h3>\n

Xiaoxiao Guo, Hui Wu, Yu Cheng<\/strong>, Steven Rennie, Rogerio Schmidt Feris<\/p>\n

Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #93<\/h3>\n

Daya Guo, Duyu Tang<\/a>, Nan Duan<\/a>, Ming Zhou<\/a>, Jian Yin<\/p>\n

Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #94<\/h3>\n

Yizhe Zhang<\/a>, Michel Galley<\/a>, Jianfeng Gao<\/a>, Zhe Gan<\/strong>, Xiujun Li<\/a>, Chris Brockett<\/a>, Bill Dolan<\/a><\/p>\n

Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #85<\/h3>\n

Tianyu He, Tao Qin<\/a>, Tie-Yan Liu<\/a>, Yingce Xia<\/strong>, Xu Tan<\/a>, Di He<\/a>, Zhibo Chen<\/p>\n

Local Differential Privacy for Evolving Data<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\n

Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/strong><\/p>\n

Precision and Recall for Time Series<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #116<\/h3>\n

Nesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich<\/p>\n

Supervising Unsupervised Learning<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #164<\/h3>\n

Vikas Garg, Adam Kalai<\/a><\/p>\n

Turbo Learning for Captionbot and Drawingbot<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #54<\/h3>\n

Qiuyuan Huang<\/a>, Pengchuan Zhang<\/a>, Oliver Wu, Lei Zhang<\/a><\/p>\n

\n

Wednesday, December 5, 2018<\/h2>\n
\n

Adversarial Text Generation via Feature-Mover’s Distance<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #129<\/h3>\n

Liqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan<\/strong>, Haichao Zhang, Yizhe Zhang<\/a>, Lawrence Carin<\/p>\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #159<\/h3>\n

Sampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/strong>, Zhiwei Steven Wu<\/p>\n

Constructing Unrestricted Adversarial Examples with Generative Models<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #149<\/h3>\n

Yang Song, Rui Shu, Nate Kushman<\/a>, Stefano Ermon<\/p>\n

Global Non-convex Optimization with Discretized Diffusions<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #18<\/h3>\n

Murat A. Erdogdu, Lester Mackey<\/a>, Ohad Shamir<\/p>\n

Inexact trust-region algorithms on Riemannian manifolds<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #15<\/h3>\n

Hiroyuki Kasai, Bamdev Mishra<\/strong><\/p>\n

Is Q-Learning Provably Efficient?<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\n

Chi Jin, Zeyuan Allen-Zhu<\/a>, Sebastien Bubeck<\/a>, Michael Jordon<\/p>\n

M-Walk: Learning to Walk over Graphs with Monte Carlo Tree Search<\/a>
\n10:45 AM-12:45 PM | Room 210&230 | AB #164<\/h3>\n

Yelong Shen<\/strong>, Jianshu Chen, Po-Sen Huang, Yuqing Guo<\/strong>, Jianfeng Gao<\/a><\/p>\n

On Oracle-Efficient PAC RL with Rich Observations<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #111<\/h3>\n

Christoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a><\/p>\n

On the Local Hessian in Back-propagation<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #43<\/h3>\n

Huishuai Zhang<\/a>, Wei Chen<\/a>, Tie-Yan Liu<\/a><\/p>\n

Recurrent Transformer Networks for Semantic Correspondence<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #119<\/h3>\n

Seungryong Kim, Stephen Lin<\/strong>, SANG RYUL JEON, Dongbo Min, Kwanghoon Sohn<\/p>\n

Universal Growth in Production Economies<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\n

Simina Branzei, Ruta Mehta, Noam Nisan<\/strong><\/p>\n

Weakly Supervised Dense Event Captioning in Videos<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #125<\/h3>\n

Xuguang Duan, Wenbing Huang, Chuang Gan, Jingdong Wang<\/a>, Wenwu Zhu, Junzhou Huang<\/p>\n

Natasha 2: Faster Non-Convex Optimization Than SGD<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #50<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/p>\n

Coupled Variational Bayes via Optimization Embedding<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #11<\/h3>\n

Bo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao<\/a>, Le Song<\/p>\n

Dual Policy Iteration<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #124<\/h3>\n

Wen Sun, Geoffrey Gordon<\/a>, Wen Sun, J. Andrew Bagnell<\/p>\n

Probabilistic Matrix Factorization for Automated Machine Learning<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\n

Nicolo Fusi<\/a>, Rishit Sheth<\/a>, Melih Elibol<\/strong><\/p>\n

NEON2: Finding Local Minima via First-Order Oracles<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #45<\/h3>\n

Zeyuan Allen-Zhu<\/a>, Yuanzhi Li<\/p>\n

Teaching Inverse Reinforcement Learners via Features and Demonstrations<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #167<\/h3>\n

Luis Haug, Sebastian Tschiatschek<\/a>, Adish Singla<\/p>\n

\n

Thursday, December 6, 2018<\/h2>\n
\n

Contextual bandits with surrogate losses: Margin bounds and efficient algorithms<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\n

Dylan Foster, Akshay Krishnamurthy<\/a><\/p>\n

FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network<\/a>
\n10:45 AM – 12:45 PM | Room 210&230 AB #89<\/h3>\n

Aditya Kusupati<\/strong>, Manish Singh,\u00a0Kush Bhatia, Ashish Kumar, \u00a0 Prateek Jain<\/a>, Manik Varma<\/a><\/p>\n

Gaussian Process Prior Variational Autoencoders<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #63<\/h3>\n

Nicolo Fusi<\/a>, Luca Saglietti<\/strong>, Francesco Paolo Casale<\/a>, Adrian Dalca, Jennifer Listgarten<\/p>\n

Learning to Teach with Dynamic Loss Functions<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #155<\/h3>\n

Tao Qin<\/a>, Tie-Yan Liu<\/a>, Fei Tian<\/a>, Yingce Xia<\/strong>, Lijun Wu, Yingce Xia, Lai Jian-Huang<\/p>\n

Byzantine Stochastic Gradient Descent<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #164<\/h3>\n

Dan Alistarh, Zeyuan Allen-Zhu<\/a>, Jerry Li<\/p>\n

Towards Deep Conversational Recommendations<\/a>
\n10:45 AM-12:45 PM | Room 210&230 AB #118<\/h3>\n

Raymond Li, Samira Ebrahimi Kahou<\/a>, Hannes Schulz<\/a>,Vincent Michalski, Laurent Charlin, Chris Pal<\/p>\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\n

Kevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Yin Tat Lee, Laurent Massoulie<\/p>\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #63<\/h3>\n

Raghav Somani<\/strong>, Chirag Gupta, Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/p>\n

Community Exploration: From Offline Optimization to Online Learning<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\n

Xiaowei Chen, Weiran Huang, Wei Chen<\/a>, John C.S. Lui<\/p>\n

Constrained Graph Variational Autoencoders for Molecule Design<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #103<\/h3>\n

Qi Liu, Miltos Allamanis<\/a>, Marc Brockschmidt<\/a>, Alexander Gaunt<\/a><\/p>\n

How To Make the Gradients Small Stochastically<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #74<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/p>\n

Learning Beam Search Policies via Imitation Learning<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB#104<\/h3>\n

Renato Negrinho, Matthew Gormley, Geoffrey Gordon<\/a><\/p>\n

Learning SMaLL Predictors<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #98<\/h3>\n

Vikas K. Garg, Ofer Dekel<\/a>, Lin Xiao<\/a><\/p>\n

Neural Architecture Optimization<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #123<\/h3>\n

Renqian Luo, Fei Tian<\/a>, Tao Qin<\/a>, Enhon Chen, Tie-Yan Liu<\/a><\/p>\n

Random Feature Stein Discrepancies<\/a>
\n5:00 PM-7:00 PM | Room 210&230 AB #78<\/h3>\n

Jonathan Huggins, Lester Mackey<\/a><\/p>\n

\n

Opens in a new tab<\/span><\/p>\n

Local Differential Privacy for Evolving Data
\nTuesday, December 4, 2018 | 3:35 PM\u20133:40 PM | Room 517CD<\/h3>\n

Matthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/a><\/strong><\/p>\n

Bounded-Loss Private Prediction Markets
\nTuesday, December 4, 2018 | 4:05 PM\u20134:10 PM | Room 517CD<\/h3>\n

Rafael Frongillo, Bo Waggoner<\/a><\/strong><\/p>\n

Precision and Recall for Time Series
\nTuesday, December 4, 2018 | 4:50 PM\u20134:55 PM | Room 220CD<\/h3>\n

Nesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich<\/p>\n

Supervising Unsupervised Learning
\nTuesday, December 4, 2018 | 4:55 PM\u20135:00 PM | Room 517CD<\/h3>\n

Vikas Garg, Adam Kalai<\/a><\/strong><\/p>\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
\nWednesday, December 5, 2018 | 9:45 AM\u20139:50 AM | Room 220CD<\/h3>\n

Sampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/a><\/strong>, Zhiwei Steven Wu<\/p>\n

Recurrent Transformer Networks for Semantic Correspondence
\nWednesday, December 5, 2018 | 10:20 AM\u201310:25 AM | Room 220E<\/h3>\n

Seungryong Kim, Stephen Lin<\/a><\/strong>, Sang Ryul Jeon, Dongbo Min, Kwanghoon Sohn<\/p>\n

On Oracle-Efficient PAC RL with Rich Observations
\nWednesday, December 5, 2018 | 10:25 AM\u201310:30 AM | Room 220CD<\/h3>\n

Christoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a><\/strong><\/p>\n

Natasha 2: Faster Non-Convex Optimization Than SGD
\nWednesday, December 5, 2018 | 4:40 PM\u20134:45 PM | Room 517CD<\/h3>\n

Zeyuan Allen-Zhu<\/a><\/strong><\/p>\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds
\nThursday, December 6, 2018 | 4:55 PM\u20135:00 PM | Room 220CD<\/h3>\n

Raghav Somani,<\/strong> Chirag Gupta,<\/strong> Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/strong>Opens in a new tab<\/span><\/p>\n

On the Dimensionality of Word Embedding
\nThursday, December 6, 2018 | 10:05AM \u2013 10:20AM | Room 220E<\/h3>\n

Zi Yin, Yuanyuan Shen<\/strong><\/p>\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>
\nThursday, December 6, 2018 | 3:50 PM\u20134:05 PM | Room 517CD<\/h3>\n

Kevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Laurent Massouli\u00e9, Yin Tat LeeOpens in a new tab<\/span><\/p>\n

2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)<\/a>
\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Invited speaker: Manik Varma<\/a><\/p>\n

MLSys: Workshop on Systems for ML and Open Source Software<\/a>
\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Accepted paper: Matteo Interlandi,\u00a0Sergiy Matusevych,\u00a0Saeed Amizadeh, Shauheen Zahirazami, Markus Weimer<\/strong> | Machine Learning at Microsoft with ML.NET<\/p>\n

Accepted paper:\u00a0Gyeong-In Yu,\u00a0Saeed Amizadeh<\/b>,\u00a0Byung-Gon Chun, Markus Weimer, Matteo Interlandi<\/b> | Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach<\/p>\n

Accepted paper: Yaoqing Yang, Matteo Interlandi<\/b>, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer<\/b> | Coded Elastic Computing<\/p>\n

2nd Conversational AI: \u201cToday’s Practice and Tomorrow’s Potential\u201d<\/a>
\nFriday, December 7, 2018 | 9:00 AM-5:30 PM<\/h3>\n

Accepted paper: Elnaz Nouri<\/a>, Ehsan Hosseini-Asl | Toward Scalable Neural Dialogue State Tracking Model<\/p>\n

Workshop on Security in Machine Learning<\/a>
\nFriday, December 7, 2018 | 11:00 AM-1:30 PM<\/h3>\n

Keynote: danah boyd<\/a><\/p>\n

Interpretability and Robustness in Audio, Speech, and Language<\/a>
\nSaturday, December 8, 2018 | 9:00 AM-9:30 AM<\/h3>\n

Invited Speaker 1: Rich Caruana<\/a><\/p>\n

Relational Representation Learning<\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

10:15 AM spotlight talk: Saeed Amizadeh |<\/strong> A Neural Framework for Learning DAG to DAG Translation
\n<\/strong><\/p>\n

Privacy Preserving Machine Learning<\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Poster: Bolin Ding, Janardhan Kulkarni and Sergey Yekhanin<\/strong> | A Distributed Algorithm For Differentially Private Heavy Hitters <\/a><\/p>\n

Poster: Joshua Allen, <\/strong>Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olya Ohrimenko and Sergey Yekhanin<\/strong> | An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors <\/a><\/p>\n

Second Workshop on Machine Learning for Creativity and Design<\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Poster: Khyatti Gupta, Sonam Damani, Kedhar Nath Narahari | <\/strong>Using AI to Design Stone Jewelry<\/p>\n

Wordplay: Reinforcement and Language Learning in Text-based Games<\/a>
\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\n

Invited speaker: Katja Hofmann<\/strong><\/p>\n

Machine Learning Open Source Software 2018: Sustainable communities<\/a>
\nSaturday, December 8, 2018 | 8:30 AM-5:35 PM<\/h3>\n

11:00AM poster: Mayank Meghwankshi<\/strong>, Pratik Jawanpuria<\/strong>, Anoop Kunchukuttan<\/strong>, Hiroyuki Kasai, Bamdev Michra<\/strong>, McTorch | a manifold optimization library for deep learning<\/p>\n

11:00AM poster: Markus Weimer<\/a> | Machine Learning at Microsoft with ML.NETOpens in a new tab<\/span><\/p>\n

Booth Demos<\/h2>\n

Come by our booth (#203) to see demos of our latest research. See schedule below:<\/p>\n

<\/div>\n

Sunday, December 2<\/h3>\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
10:00 AM\u201310:30 AM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:30 PM\u20131:15 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:15 PM\u20132:00 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
4:00 PM\u20134:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
6:30 PM\u20137:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Monday, December 3<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
10:30 AM\u201311:00 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:00 PM\u20131:45 PM<\/td>\nMulti-Word Imput<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:45 PM\u20132:30 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
4:30 PM\u20135:00 PM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
6:30 PM\u20137:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
7:30 PM\u20138:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Tuesday, December 4<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
9:40 AM\u201310:05 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:15 PM<\/td>\nMulti-Word Imput<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:05 PM\u20133:30 PM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Wednesday, December 5<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
9:20 AM\u20139:45 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:15 PM<\/td>\nTextWorld<\/td>\n<\/tr>\n
<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:05 PM\u20133:30 PM<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Thursday, December 6<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
9:20 AM\u20139:45 AM<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nMulti-Word Imput<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:15 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:05 PM\u20133:30 PM<\/td>\nInfer.NET – Y. Zaykov<\/td>\n<\/tr>\n
<\/td>\nRuuh<\/td>\n<\/tr>\n
<\/td>\nAI for Good<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Friday, December 7<\/h3>\n\n\n\n\n\n\n\n\n\n
Time (EST)<\/strong><\/td>\nDemo<\/strong><\/td>\n<\/tr>\n
10:30 AM\u201311:00 AM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:00 PM\u201312:45 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
12:45 PM\u20131:30 PM<\/td>\nGesturePod<\/td>\n<\/tr>\n
<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
1:30 PM\u20132:00 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n
3:00 PM\u20133:30 PM<\/td>\nAzure Machine Learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
<\/div>\n

Conference Demo Sessions<\/h2>\n

ML on Resource Constrained Edge Devices \u2013 GesturePod! (opens in new tab)<\/span><\/a>
\nSunday, December 2, 2018 | 2:00 PM\u20136:30 PM | Room 510ABCD<\/h3>\n

Shishir G. Patil, Don Kurian Dennis, Harsha Vardhan Simhadri, Prateek Jain (opens in new tab)<\/span><\/a>
\n<\/strong><\/p>\n

Ruuh: A Deep Learning Based Conversational Social Agent (opens in new tab)<\/span><\/a>
\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D3<\/h3>\n

Manoj Chinnakotla, Kedhar Narahari, Nitya Raviprakash, Umang Gupta, Ankush Chatterjee, Sneha Magapu, Sonam Damani, Abhishek Mathur, Puneet Agrawal, Meghana Joshi, Khyatti Gupta<\/strong><\/p>\n

TextWorld: A Learning Environment for Text-based Games (opens in new tab)<\/span><\/a>
\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D10<\/h3>\n

Eric Yuan (opens in new tab)<\/span><\/a>, Wendy Tay (opens in new tab)<\/span><\/a>, Marc-Alexandre C\u00f4t\u00e9 (opens in new tab)<\/span><\/a><\/p>\n

Multi-Word Imputation and Sentence Expansion (opens in new tab)<\/span><\/a>
\nWednesday, December 5, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D7<\/h3>\n

Douglas Orr, Osman Ramadan, <\/strong>Dmitry Stratiychuk, B\u0142a\u017cej Czapp<\/strong>Opens in a new tab<\/span><\/p>\n

\t\t\t

\n\t\t\t
\n\t\t\t\t\n
\n\t
\n\t\t

\n\t\t\t\t\t\t\t NeurIPS Conference Analytics<\/a>\n\t\t\t\t\t<\/h3>\n\n\t\t
\n\t\t\t
\n\t\t\t\t\t\t\t\tMicrosoft Academic | November 23, 2018

<\/h3>

The Microsoft Academic Graph makes it possible to gain analytic insights about any of the entities within it: publications, authors, institutions, topics, journals, and conferences.\t\t\t<\/div>\n\t\t<\/div>\n\n\t<\/div>\n<\/article>\n<\/p>\t\t\t<\/div>\n\t\t<\/div>\n\t\tOpens in a new tab<\/span><\/p>\n","tab-content":[{"id":0,"name":"About","content":"Microsoft is excited to be a Diamond sponsor of the 32nd annual conference on Neural Information Processing Systems<\/a>. Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities<\/a> with Microsoft.\r\n

Program Chair<\/h2>\r\nHanna Wallach<\/a>\r\n
\r\n

Tutorial Chair<\/h2>\r\n<\/div>\r\n
\r\n\r\nJenn Wortman Vaughan<\/a>\r\n\r\n<\/div>\r\n

Workshop Organizers<\/h2>\r\nPrateek Jain<\/a> | 2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)<\/a>\r\n\r\nAbhishek Gupta | AI for social good<\/a>\r\n\r\nEvelyne Viegas<\/a> | CiML 2018 - Machine Learning competitions \"in the wild\": Playing in the real world or in real time<\/a>\r\n\r\nRich Caruana<\/a> | Critiquing and Correcting Trends in Machine Learning<\/a>\r\n\r\nTristan Naumann<\/a> | Machine Learning for Health (ML4H): Moving beyond supervised learning in healthcare<\/a>\r\n\r\nSiddhartha Sen<\/a> | MLSys: Workshop on Systems for ML and Open Source Software<\/a>\r\n\r\nOlya Ohrimenko<\/a> | Privacy Preserving Machine Learning<\/a>\r\n\r\nMarc-Alexandre C\u00f4t\u00e9<\/a>, Wendy Tay<\/a>, Adam Trischler<\/a>, Hal Daum\u00e9 III<\/a>, Nate Kushman<\/a>, Alessandro Sordoni<\/a> | Wordplay: Reinforcement and Language Learning in Text-based Games<\/a>\r\n

Volunteer Workflow Team<\/h2>\r\nChinmay Singh<\/a>"},{"id":1,"name":"Posters","content":"
\r\n\r\n

Tuesday, December 4, 2018<\/h2>\r\n\r\n
\r\n\r\n

Adversarial Multiple Source Domain Adaptation<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #107<\/h3>\r\nHan Zhao, Shanghang Zhang, Guanhang Wu, Jose M. F. Moura, Joao P. Costeira, Geoffrey Gordon<\/a>\r\n

FRAGE: Frequency-Agnostic Word Representation<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #153<\/h3>\r\nChengyue Gong, Di He<\/a>, Xu Tan<\/a>, Tao Qin<\/a>, Liwei Wang, Tie-Yan Liu<\/a>\r\n

Frequency-Domain Dynamic Pruning for Convolutional Neural Networks<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #67<\/h3>\r\nZhenhua Liu, Jizheng Xu, Xiulian Peng<\/a>, Ruiqin Xiong\r\n

Heterogeneous Bitwidth Binarization in Convolutional Neural Networks<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #69<\/h3>\r\nJosh Fromm, Shwetak Patel, Matthai Philipose<\/a>\r\n

Multiple Instance Learning for Efficient Sequential Data Classification on Resource-constrained Devices<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\r\nDon Dennis, Chirag Pabbaraju<\/strong>, Harsha Vardhan Simhadri<\/a>, Prateek Jain<\/a>\r\n

Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #73<\/h3>\r\nMinjia Zhang<\/a>, Xiaodong Liu<\/a>, Wenhan Wang<\/strong>, Jianfeng Gao<\/a>, Yuxiong He<\/a>\r\n

On the Dimensionality of Word Embedding<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #110<\/h3>\r\nZi Yin, Yuanyuan Shen<\/strong>\r\n

The Lingering of Gradients: How to Reuse Gradients Over Time<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #2<\/h3>\r\nZeyuan Allen-Zhu<\/a>\r\n

Towards Text Generation with Adversarially Learned Neural Outlines<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #14<\/h3>\r\nSandeep Subramanian, Sai Rajeswar Mudumba, Adam Trischler<\/a>, Alessandro Sordoni<\/a>, Aaron Courville, Chris Pal\r\n

A Dual Framework for Low-rank Tensor Completion<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #146<\/h3>\r\nMadhav Nimishakavi, Bamdev Mishra<\/a>, Pratik Kumar Jawanpuria<\/strong><\/a>\r\n

Bounded-Loss Private Prediction Markets<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #28<\/h3>\r\nRafael Frongillo, Bo Waggoner<\/strong>\r\n

Contamination Attacks in Multi-Party Machine Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #158<\/h3>\r\nJamie Hayes, Olya Ohrimenko<\/a>\r\n

Dialog-based Interactive Image Retrieval<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #55<\/h3>\r\nXiaoxiao Guo, Hui Wu, Yu Cheng<\/strong>, Steven Rennie, Rogerio Schmidt Feris\r\n

Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #93<\/h3>\r\nDaya Guo, Duyu Tang<\/a>, Nan Duan<\/a>, Ming Zhou<\/a>, Jian Yin\r\n

Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #94<\/h3>\r\nYizhe Zhang<\/a>, Michel Galley<\/a>, Jianfeng Gao<\/a>, Zhe Gan<\/strong>, Xiujun Li<\/a>, Chris Brockett<\/a>, Bill Dolan<\/a>\r\n

Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #85<\/h3>\r\nTianyu He, Tao Qin<\/a>, Tie-Yan Liu<\/a>, Yingce Xia<\/strong>, Xu Tan<\/a>, Di He<\/a>, Zhibo Chen\r\n

Local Differential Privacy for Evolving Data<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\r\nMatthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/strong>\r\n

Precision and Recall for Time Series<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #116<\/h3>\r\nNesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich\r\n

Supervising Unsupervised Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #164<\/h3>\r\nVikas Garg, Adam Kalai<\/a>\r\n

Turbo Learning for Captionbot and Drawingbot<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #54<\/h3>\r\nQiuyuan Huang<\/a>, Pengchuan Zhang<\/a>, Oliver Wu, Lei Zhang<\/a>\r\n\r\n
\r\n\r\n

Wednesday, December 5, 2018<\/h2>\r\n\r\n
\r\n\r\n

Adversarial Text Generation via Feature-Mover's Distance<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #129<\/h3>\r\nLiqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan<\/strong>, Haichao Zhang, Yizhe Zhang<\/a>, Lawrence Carin\r\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #159<\/h3>\r\nSampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/strong>, Zhiwei Steven Wu\r\n

Constructing Unrestricted Adversarial Examples with Generative Models<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #149<\/h3>\r\nYang Song, Rui Shu, Nate Kushman<\/a>, Stefano Ermon\r\n

Global Non-convex Optimization with Discretized Diffusions<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #18<\/h3>\r\nMurat A. Erdogdu, Lester Mackey<\/a>, Ohad Shamir\r\n

Inexact trust-region algorithms on Riemannian manifolds<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #15<\/h3>\r\nHiroyuki Kasai, Bamdev Mishra<\/strong>\r\n

Is Q-Learning Provably Efficient?<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\r\nChi Jin, Zeyuan Allen-Zhu<\/a>, Sebastien Bubeck<\/a>, Michael Jordon\r\n

M-Walk: Learning to Walk over Graphs with Monte Carlo Tree Search<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 | AB #164<\/h3>\r\nYelong Shen<\/strong>, Jianshu Chen, Po-Sen Huang, Yuqing Guo<\/strong>, Jianfeng Gao<\/a>\r\n

On Oracle-Efficient PAC RL with Rich Observations<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #111<\/h3>\r\nChristoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a>\r\n

On the Local Hessian in Back-propagation<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #43<\/h3>\r\nHuishuai Zhang<\/a>, Wei Chen<\/a>, Tie-Yan Liu<\/a>\r\n

Recurrent Transformer Networks for Semantic Correspondence<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #119<\/h3>\r\nSeungryong Kim, Stephen Lin<\/strong>, SANG RYUL JEON, Dongbo Min, Kwanghoon Sohn\r\n

Universal Growth in Production Economies<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #72<\/h3>\r\nSimina Branzei, Ruta Mehta, Noam Nisan<\/strong>\r\n

Weakly Supervised Dense Event Captioning in Videos<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #125<\/h3>\r\nXuguang Duan, Wenbing Huang, Chuang Gan, Jingdong Wang<\/a>, Wenwu Zhu, Junzhou Huang\r\n

Natasha 2: Faster Non-Convex Optimization Than SGD<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #50<\/h3>\r\nZeyuan Allen-Zhu<\/a>\r\n

Coupled Variational Bayes via Optimization Embedding<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #11<\/h3>\r\nBo Dai, Hanjun Dai, Niao He, Weiyang Liu, Zhen Liu, Jianshu Chen, Lin Xiao<\/a>, Le Song\r\n

Dual Policy Iteration<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #124<\/h3>\r\nWen Sun, Geoffrey Gordon<\/a>, Wen Sun, J. Andrew Bagnell\r\n

Probabilistic Matrix Factorization for Automated Machine Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\r\nNicolo Fusi<\/a>, Rishit Sheth<\/a>, Melih Elibol<\/strong>\r\n

NEON2: Finding Local Minima via First-Order Oracles<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #45<\/h3>\r\nZeyuan Allen-Zhu<\/a>, Yuanzhi Li\r\n

Teaching Inverse Reinforcement Learners via Features and Demonstrations<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #167<\/h3>\r\nLuis Haug, Sebastian Tschiatschek<\/a>, Adish Singla\r\n\r\n
\r\n\r\n

Thursday, December 6, 2018<\/h2>\r\n\r\n
\r\n\r\n

Contextual bandits with surrogate losses: Margin bounds and efficient algorithms<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #165<\/h3>\r\nDylan Foster, Akshay Krishnamurthy<\/a>\r\n

FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network<\/a>\r\n10:45 AM - 12:45 PM | Room 210&230 AB #89<\/h3>\r\nAditya Kusupati<\/strong>, Manish Singh,\u00a0Kush Bhatia, Ashish Kumar, \u00a0 Prateek Jain<\/a>, Manik Varma<\/a>\r\n

Gaussian Process Prior Variational Autoencoders<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #63<\/h3>\r\nNicolo Fusi<\/a>, Luca Saglietti<\/strong>, Francesco Paolo Casale<\/a>, Adrian Dalca, Jennifer Listgarten\r\n

Learning to Teach with Dynamic Loss Functions<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #155<\/h3>\r\nTao Qin<\/a>, Tie-Yan Liu<\/a>, Fei Tian<\/a>, Yingce Xia<\/strong>, Lijun Wu, Yingce Xia, Lai Jian-Huang\r\n

Byzantine Stochastic Gradient Descent<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #164<\/h3>\r\nDan Alistarh, Zeyuan Allen-Zhu<\/a>, Jerry Li\r\n

Towards Deep Conversational Recommendations<\/a>\r\n10:45 AM-12:45 PM | Room 210&230 AB #118<\/h3>\r\nRaymond Li, Samira Ebrahimi Kahou<\/a>, Hannes Schulz<\/a>,Vincent Michalski, Laurent Charlin, Chris Pal\r\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #15<\/h3>\r\nKevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Yin Tat Lee, Laurent Massoulie\r\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #63<\/h3>\r\nRaghav Somani<\/strong>, Chirag Gupta, Prateek Jain<\/a>, Praneeth Netrapalli<\/a>\r\n

Community Exploration: From Offline Optimization to Online Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #153<\/h3>\r\nXiaowei Chen, Weiran Huang, Wei Chen<\/a>, John C.S. Lui\r\n

Constrained Graph Variational Autoencoders for Molecule Design<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #103<\/h3>\r\nQi Liu, Miltos Allamanis<\/a>, Marc Brockschmidt<\/a>, Alexander Gaunt<\/a>\r\n

How To Make the Gradients Small Stochastically<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #74<\/h3>\r\nZeyuan Allen-Zhu<\/a>\r\n

Learning Beam Search Policies via Imitation Learning<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB#104<\/h3>\r\nRenato Negrinho, Matthew Gormley, Geoffrey Gordon<\/a>\r\n

Learning SMaLL Predictors<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #98<\/h3>\r\nVikas K. Garg, Ofer Dekel<\/a>, Lin Xiao<\/a>\r\n

Neural Architecture Optimization<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #123<\/h3>\r\nRenqian Luo, Fei Tian<\/a>, Tao Qin<\/a>, Enhon Chen, Tie-Yan Liu<\/a>\r\n

Random Feature Stein Discrepancies<\/a>\r\n5:00 PM-7:00 PM | Room 210&230 AB #78<\/h3>\r\nJonathan Huggins, Lester Mackey<\/a>\r\n\r\n
"},{"id":2,"name":"Spotlight Sessions","content":"

Local Differential Privacy for Evolving Data\r\nTuesday, December 4, 2018 | 3:35 PM\u20133:40 PM | Room 517CD<\/h3>\r\nMatthew Joseph, Aaron Roth, Jonathan Ullman, Bo Waggoner<\/a><\/strong>\r\n

Bounded-Loss Private Prediction Markets\r\nTuesday, December 4, 2018 | 4:05 PM\u20134:10 PM | Room 517CD<\/h3>\r\nRafael Frongillo, Bo Waggoner<\/a><\/strong>\r\n

Precision and Recall for Time Series\r\nTuesday, December 4, 2018 | 4:50 PM\u20134:55 PM | Room 220CD<\/h3>\r\nNesime Tatbul, Tae Jun Lee<\/strong>, Stan Zdonik, Mejbah Alam, Justin Gottschlich\r\n

Supervising Unsupervised Learning\r\nTuesday, December 4, 2018 | 4:55 PM\u20135:00 PM | Room 517CD<\/h3>\r\nVikas Garg, Adam Kalai<\/a><\/strong>\r\n

A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem\r\nWednesday, December 5, 2018 | 9:45 AM\u20139:50 AM | Room 220CD<\/h3>\r\nSampath Kannan, Jamie Morgenstern, Aaron Roth, Bo Waggoner<\/a><\/strong>, Zhiwei Steven Wu\r\n

Recurrent Transformer Networks for Semantic Correspondence\r\nWednesday, December 5, 2018 | 10:20 AM\u201310:25 AM | Room 220E<\/h3>\r\nSeungryong Kim, Stephen Lin<\/a><\/strong>, Sang Ryul Jeon, Dongbo Min, Kwanghoon Sohn\r\n

On Oracle-Efficient PAC RL with Rich Observations\r\nWednesday, December 5, 2018 | 10:25 AM\u201310:30 AM | Room 220CD<\/h3>\r\nChristoph Dann, Nan Jiang, Akshay Krishnamurthy<\/a>, Alekh Agarwal<\/a>, John Langford<\/a>, Robert Schapire<\/a><\/strong>\r\n

Natasha 2: Faster Non-Convex Optimization Than SGD\r\nWednesday, December 5, 2018 | 4:40 PM\u20134:45 PM | Room 517CD<\/h3>\r\nZeyuan Allen-Zhu<\/a><\/strong>\r\n

Support Recovery for Orthogonal Matching Pursuit: Upper and Lower bounds\r\nThursday, December 6, 2018 | 4:55 PM\u20135:00 PM | Room 220CD<\/h3>\r\nRaghav Somani,<\/strong> Chirag Gupta,<\/strong> Prateek Jain<\/a>, Praneeth Netrapalli<\/a><\/strong>"},{"id":3,"name":"Oral Presentations","content":"

On the Dimensionality of Word Embedding\r\nThursday, December 6, 2018 | 10:05AM \u2013 10:20AM | Room 220E<\/h3>\r\nZi Yin, Yuanyuan Shen<\/strong>\r\n

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks<\/a>\r\nThursday, December 6, 2018 | 3:50 PM\u20134:05 PM | Room 517CD<\/h3>\r\nKevin Scaman, Francis Bach, Sebastien Bubeck<\/a>, Laurent Massouli\u00e9, Yin Tat Lee"},{"id":4,"name":"Workshops","content":"

2nd Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD 2)<\/a>\r\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nInvited speaker: Manik Varma<\/a>\r\n

MLSys: Workshop on Systems for ML and Open Source Software<\/a>\r\nFriday, December 7, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nAccepted paper: Matteo Interlandi,\u00a0Sergiy Matusevych,\u00a0Saeed Amizadeh, Shauheen Zahirazami, Markus Weimer<\/strong> | Machine Learning at Microsoft with ML.NET\r\n\r\nAccepted paper:\u00a0Gyeong-In Yu,\u00a0Saeed Amizadeh<\/b>,\u00a0Byung-Gon Chun, Markus Weimer, Matteo Interlandi<\/b> | Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach\r\n\r\nAccepted paper: Yaoqing Yang, Matteo Interlandi<\/b>, Pulkit Grover, Soummya Kar, Saeed Amizadeh, Markus Weimer<\/b> | Coded Elastic Computing\r\n

2nd Conversational AI: \u201cToday's Practice and Tomorrow's Potential\u201d<\/a>\r\nFriday, December 7, 2018 | 9:00 AM-5:30 PM<\/h3>\r\nAccepted paper: Elnaz Nouri<\/a>, Ehsan Hosseini-Asl | Toward Scalable Neural Dialogue State Tracking Model\r\n

Workshop on Security in Machine Learning<\/a>\r\nFriday, December 7, 2018 | 11:00 AM-1:30 PM<\/h3>\r\nKeynote: danah boyd<\/a>\r\n

Interpretability and Robustness in Audio, Speech, and Language<\/a>\r\nSaturday, December 8, 2018 | 9:00 AM-9:30 AM<\/h3>\r\nInvited Speaker 1: Rich Caruana<\/a>\r\n

Relational Representation Learning<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\n10:15 AM spotlight talk: Saeed Amizadeh |<\/strong> A Neural Framework for Learning DAG to DAG Translation\r\n<\/strong>\r\n

Privacy Preserving Machine Learning<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nPoster: Bolin Ding, Janardhan Kulkarni and Sergey Yekhanin<\/strong> | A Distributed Algorithm For Differentially Private Heavy Hitters <\/a>\r\n\r\nPoster: Joshua Allen, <\/strong>Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olya Ohrimenko and Sergey Yekhanin<\/strong> | An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors <\/a>\r\n

Second Workshop on Machine Learning for Creativity and Design<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nPoster: Khyatti Gupta, Sonam Damani, Kedhar Nath Narahari | <\/strong>Using AI to Design Stone Jewelry\r\n

Wordplay: Reinforcement and Language Learning in Text-based Games<\/a>\r\nSaturday, December 8, 2018 | 8:00 AM-6:30 PM<\/h3>\r\nInvited speaker: Katja Hofmann<\/strong>\r\n

Machine Learning Open Source Software 2018: Sustainable communities<\/a>\r\nSaturday, December 8, 2018 | 8:30 AM-5:35 PM<\/h3>\r\n11:00AM poster: Mayank Meghwankshi<\/strong>, Pratik Jawanpuria<\/strong>, Anoop Kunchukuttan<\/strong>, Hiroyuki Kasai, Bamdev Michra<\/strong>, McTorch | a manifold optimization library for deep learning\r\n\r\n11:00AM poster: Markus Weimer<\/a> | Machine Learning at Microsoft with ML.NET"},{"id":5,"name":"Demonstrations","content":"

Booth Demos<\/h2>\r\nCome by our booth (#203) to see demos of our latest research. See schedule below:\r\n
<\/div>\r\n

Sunday, December 2<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
10:00 AM\u201310:30 AM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:30 PM\u20131:15 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:15 PM\u20132:00 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
4:00 PM\u20134:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
6:30 PM\u20137:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Monday, December 3<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
10:30 AM\u201311:00 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:00 PM\u20131:45 PM<\/td>\r\nMulti-Word Imput<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:45 PM\u20132:30 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
4:30 PM\u20135:00 PM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
6:30 PM\u20137:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
7:30 PM\u20138:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Tuesday, December 4<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
9:40 AM\u201310:05 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:15 PM<\/td>\r\nMulti-Word Imput<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:05 PM\u20133:30 PM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Wednesday, December 5<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
9:20 AM\u20139:45 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:15 PM<\/td>\r\nTextWorld<\/td>\r\n<\/tr>\r\n
<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:05 PM\u20133:30 PM<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Thursday, December 6<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
9:20 AM\u20139:45 AM<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nMulti-Word Imput<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:15 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:05 PM\u20133:30 PM<\/td>\r\nInfer.NET - Y. Zaykov<\/td>\r\n<\/tr>\r\n
<\/td>\r\nRuuh<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAI for Good<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Friday, December 7<\/h3>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Time (EST)<\/strong><\/td>\r\nDemo<\/strong><\/td>\r\n<\/tr>\r\n
10:30 AM\u201311:00 AM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:00 PM\u201312:45 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
12:45 PM\u20131:30 PM<\/td>\r\nGesturePod<\/td>\r\n<\/tr>\r\n
<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
1:30 PM\u20132:00 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n
3:00 PM\u20133:30 PM<\/td>\r\nAzure Machine Learning<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
<\/div>\r\n

Conference Demo Sessions<\/h2>\r\n

ML on Resource Constrained Edge Devices \u2013 GesturePod!<\/a>\r\nSunday, December 2, 2018 | 2:00 PM\u20136:30 PM | Room 510ABCD<\/h3>\r\nShishir G. Patil, Don Kurian Dennis, Harsha Vardhan Simhadri, Prateek Jain<\/a>\r\n<\/strong>\r\n

Ruuh: A Deep Learning Based Conversational Social Agent<\/a>\r\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D3<\/h3>\r\nManoj Chinnakotla, Kedhar Narahari, Nitya Raviprakash, Umang Gupta, Ankush Chatterjee, Sneha Magapu, Sonam Damani, Abhishek Mathur, Puneet Agrawal, Meghana Joshi, Khyatti Gupta<\/strong>\r\n

TextWorld: A Learning Environment for Text-based Games<\/a>\r\nTuesday, December 4, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D10<\/h3>\r\nEric Yuan<\/a>, Wendy Tay<\/a>, Marc-Alexandre C\u00f4t\u00e9<\/a>\r\n

Multi-Word Imputation and Sentence Expansion<\/a>\r\nWednesday, December 5, 2018 | 10:45 AM-7:30 PM | Room 510ABCD | #D7<\/h3>\r\nDouglas Orr, Osman Ramadan, <\/strong>Dmitry Stratiychuk, B\u0142a\u017cej Czapp<\/strong>"},{"id":6,"name":"Analytics","content":"[row]\r\n[card title=\" NeurIPS Conference Analytics\" url=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/academic\/articles\/neurips-conference-analytics\/\" ]\r\nMicrosoft Academic | November 23, 2018\r\n

<\/h3>\r\nThe Microsoft Academic Graph makes it possible to gain analytic insights about any of the entities within it: publications, authors, institutions, topics, journals, and conferences.[\/card]\r\n[\/row]"}],"msr_startdate":"2018-12-02","msr_enddate":"2018-12-08","msr_event_time":"","msr_location":"Montreal, Quebec, Canada","msr_event_link":"https:\/\/nips.cc\/Register\/view-registration","msr_event_recording_link":"","msr_startdate_formatted":"December 2, 2018","msr_register_text":"Watch now","msr_cta_link":"https:\/\/nips.cc\/Register\/view-registration","msr_cta_text":"Watch now","msr_cta_bi_name":"Event Register","featured_image_thumbnail":"\"Bonsecours","event_excerpt":"Microsoft is excited to be a Diamond sponsor of the thirty-second annual conference on Neural Information Processing Systems (NIPS). Over 130 of our researchers are involved in spotlight sessions, presentations, symposiums, posters, accepted papers, and workshops at NIPS. Stop by our booth (#203) to chat with our experts, see demos of our latest research and find out about career opportunities with Microsoft.","msr_research_lab":[199560,199562,199565,199571,212740],"related-researchers":[],"msr_impact_theme":[],"related-academic-programs":[],"related-groups":[],"related-projects":[416408],"related-opportunities":[],"related-publications":[1119450,633429,543717,392960,543570,506933],"related-videos":[],"related-posts":[551157],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/508112","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-event"}],"version-history":[{"count":11,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/508112\/revisions"}],"predecessor-version":[{"id":1147068,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event\/508112\/revisions\/1147068"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/508535"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=508112"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=508112"},{"taxonomy":"msr-region","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-region?post=508112"},{"taxonomy":"msr-event-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-event-type?post=508112"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=508112"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=508112"},{"taxonomy":"msr-program-audience","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-program-audience?post=508112"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=508112"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=508112"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}