Microsoft at ICML 2019

Microsoft at ICML 2019

About

Microsoft is excited to be a Gold sponsor of ICML. We will have over 100 Microsoft attendees present at the conference. Stop by our booth (#310) to chat with our experts, see demos of our latest research and find out about career opportunities with Microsoft.

Microsoft Research attendees

Adam Smiechowski
Adith Swaminathan
Aishwarya Rameshkumar
Akshay Krishnamurthy
Alekh Agarwal
Alessandro Sordoni
Alexey Taymanov
Amy Siebenthaler
Andrew McNamara
Andrey Kolobov
Aniket Anand Deshmukh
Babak Aghazadeh
Bamdev Mishra
Besmira Nushi
Bhagirath Addepalli
Bianca Furtuna
Byron Changuion
Chandan Karadagur Ananda Reddy
Charles Jacobs
Cheng Lu
Cheng Tan
Cheng Zhang
chew-yean yam
Chicheng Zhang
Chris LaTerza
Christian Borgs
Crystal Schroeder
Daniel Wilde
Danny Garber
Di He
Ehsan Vahedi
Forough Poursabzi-Sangdeh
Hal Daumé III
Harm van Seijen
Honghao Qiu
Huishuai Zhang
Ilya Razenshteyn
Jack Gerrits
Jacob Spoelstra
Jennifer Chayes
Jennifer Wortman Vaughan
John Langford
Justin Bronder
Kamil Ciosek
Kenneth Tran
Lester Mackey
Levi Boyles
Lin Xiao
Luca Saglietti
Luke Stark
Markus Weimer
Matineh Shaker
Mehdi Fatemi
Mihaela Curmei
Mirco Milletari
Miroslav Dudik
Miruna Oprescu
Nikhil Yadala
Nikos Karampatziakis
Ofer Dekel
Patrick Lu
Patty Ryan
Paul Mineiro
Pengchuan Zhang
Philip Bachman
Philip Rosenfield
Pratik Kumar Jawanpuria
Pretesh Patel
Priya Samnerkar
Puneet Jolly
Qiuyuan Huang
Ran Gilad-Bachrach
Remi Tachet des Combes
REVANTH RAMESHKUMAR
Rich Caruana
Robin McMahon
Rodrigo Kumpera
Roland Fernandez
Romain Laroche
Ruo-Chun Tzeng
Ryan Bae
Ryan Congdon
Ryota Tomioka
Sam Devlin
Sarah Bird
Saurabh Bisht
Sebastian Kochman
Sebastian Tschiatschek
Sebastien Levy
Shauheen Zahirazami
Shize Su
Soundararajan Srinivasan
Srinagesh Sharma
Steve Ballon
Sujeeth Bharadwaj
Susan Dumais
Tao Qin
Ted Meeds
Tim Scarfe
Xiting Wang
Xu Tan
Xuan Zhao
Yihe Dong
Yingzhen Li
Yizhe Zhang
Zhe Wang

Presentations

Microsoft presentation schedule

Sunday, June 9

2:00 PM | Room 104 (Workshop)
Real World Reinforcement Learning Workshop
Organizers: John Langford, Rodrigo Kumpera, Cheng Tan, Jack Gerrits, Paul Mineiro, Alexey Taymanov

Monday, June 10

1:00 PM–3:15 PM | Grand Ballroom (Tutorial)
Neural Approaches to Conversational AI
Michel Galley, Jianfeng Gao

Tuesday, June 11

11:25 AM–11:30 AM | Grand Ballroom (Oral)
On Certifying Non-Uniform Bounds against Adversarial Attacks
Chen Liu, Ryota Tomioka, Volkan Cevher

11:40 AM–12:00 PM | Grand Ballroom (Oral)
Adversarial Examples from Computational Constraints
Sebastien Bubeck, Yin Tat Lee, Eric Price, Ilya Razenshteyn

11:40 AM–12:00 PM | Seaside Ballroom (Oral)
Contextual Memory Trees
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro

12:00 PM–12:05 PM | Room 104 (Oral)
A Composite Randomized Incremental Gradient Method
Junyu Zhang, Lin Xiao

12:00 PM–12:05 PM | Room 101 (Oral)
Stein Point Markov Chain Monte Carlo
Wilson Ye Chen, Alessandro Barp, Francois-Xavier Briol, Jackson Gorham, Mark Girolami, Lester Mackey, Chris Oates

2:00 PM–2:20 PM | Room 102 (Oral)
Generalized Approximate Survey Propagation for High-Dimensional Estimation
Carlo Lucibello, Luca Saglietti, Yue Lu

2:00 PM–2:20 PM | Grand Ballroom (Oral)
On Learning Invariant Representations for Domain Adaptation
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoff Gordon

2:00 PM–2:20 PM | Room 104 (Oral)
Safe Policy Improvement with Baseline Bootstrapping
Romain Laroche, Paul Trichelair, Remi Tachet des Combes

4:40 PM–5:00 PM | Room 102 (Oral)
Locally Private Bayesian Inference for Count Models
Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna Wallach

5:00 PM–5:05 PM | Room 102 (Oral)
Low Latency Privacy Preserving Inference
Alon Brutzkus, Ran Gilad-Bachrach, Oren Elisha

5:10 PM–5:15 PM | Room 103 (Oral)
Provably Efficient RL with Rich Observations via Latent State Decoding
Simon Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudik, John Langford

6:30 PM–9:00 PM | Pacific Ballroom (Poster #63)
On Certifying Non-Uniform Bounds against Adversarial Attacks
Chen Liu, Ryota Tomioka, Volkan Cevher

6:30 PM–9:00 PM | Pacific Ballroom (Poster #66)
Adversarial Examples from Computational Constraints
Sebastien Bubeck, Yin Tat Lee, Eric Price, Ilya Razenshteyn

6:30 PM–9:00 PM | Pacific Ballroom (Poster #71)
On Learning Invariant Representations for Domain Adaptation
Han Zhao, Remi Tachet des Combes, Kun Zhang, Geoff Gordon

6:30 PM–9:00 PM | Pacific Ballroom (Poster #97)
A Composite Randomized Incremental Gradient Method
Junyu Zhang, Lin Xiao

6:30 PM–9:00 PM | Pacific Ballroom (Poster #101)
Safe Policy Improvement with Baseline Bootstrapping
Romain Laroche, Paul Trichelair, Remi Tachet des Combes

6:30 PM–9:00 PM | Pacific Ballroom (Poster #125)
Contextual Memory Trees
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro

6:30 PM–9:00 PM | Pacific Ballroom (Poster #160)
Generalized Approximate Survey Propagation for High-Dimensional Estimation
Carlo Lucibello, Luca Saglietti, Yue Lu

6:30 PM–9:00 PM | Pacific Ballroom (Poster #175)
Locally Private Bayesian Inference for Count Models
Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna Wallach

6:30 PM–9:00 PM | Pacific Ballroom (Poster #176)
Low Latency Privacy Preserving Inference
Alon Brutzkus, Ran Gilad-Bachrach, Oren Elisha

6:30 PM–9:00 PM | Pacific Ballroom (Poster #208)
Provably Efficient RL with Rich Observations via Latent State Decoding
Simon Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudik, John Langford

6:30 PM–9:00 PM | Pacific Ballroom (Poster #216)
Stein Point Markov Chain Monte Carlo
Wilson Ye Chen, Alessandro Barp, Francois-Xavier Briol, Jackson Gorham, Mark Girolami, Lester Mackey, Chris Oates

Wednesday, June 12

11:20 AM–11:25 AM | Room 201 (Oral)
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Ted Meeds, Geoffrey Roeder, Paul Grant, Andrew Phillips, Neil Dalchau

11:25 AM–11:30 AM | Hall A (Oral)
Are Generative Classifiers More Robust to Adversarial Attacks?
Yingzhen Li, John Bradshaw, Yash Sharma

11:40 AM–12:00 PM | Hall A (Oral)
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Hernandez-Lobato, Sebastian Nowozin, Cheng Zhang

2:25 PM–2:30 PM | Room 201 (Oral)
Fast Context Adaptation via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson

2:35 PM–2:40 PM | Room 103 (Oral)
Orthogonal Random Forest for Causal Inference
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

2:40 PM–3:00 PM | Room 101 (Oral)
Variational Implicit Processes
Chao Ma, Yingzhen Li, Jose Hernandez-Lobato

3:05 PM–3:10 PM | Room 104 (Oral)
Riemannian adaptive stochastic gradient algorithms on matrix manifolds
Hiroyuki Kasai, Pratik Kumar Jawanpuria, Bamdev Mishra

4:20 PM–4:25 PM | Grand Ballroom (Oral)
Adaptive Neural Trees
Ryutaro Tanno, Kai Arulkumaran, Daniel Alexander, Antonio Criminisi, Aditya Nori

4:20 PM–4:25 PM | Room 104 (Oral)
Dead-ends and Secure Exploration in Reinforcement Learning
Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou

4:20 PM–4:25 PM | Room 103 (Oral)
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli

4:25 PM–4:30 PM | Grand Ballroom (Oral)
Connectivity-Optimized Representation Learning via Persistent Homology
Christoph Hofer, Roland Kwitt, Marc Niethammer, Mandar Dixit

4:25 PM–4:30 PM | Room 201 (Oral)
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos

6:30 PM–9:00 PM | Pacific Ballroom (Poster #3)
Are Generative Classifiers More Robust to Adversarial Attacks?
Yingzhen Li, John Bradshaw, Yash Sharma

6:30 PM–9:00 PM | Pacific Ballroom (Poster #6)
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, Jose Hernandez-Lobato, Sebastian Nowozin, Cheng Zhang

6:30 PM–9:00 PM | Pacific Ballroom (Poster #82)
Adaptive Neural Trees
Ryutaro Tanno, Kai Arulkumaran, Daniel Alexander, Antonio Criminisi, Aditya Nori

6:30 PM–9:00 PM | Pacific Ballroom (Poster #83)
Connectivity-Optimized Representation Learning via Persistent Homology
Christoph Hofer, Roland Kwitt, Marc Niethammer, Mandar Dixit

6:30 PM–9:00 PM | Pacific Ballroom (Poster #108)
Riemannian adaptive stochastic gradient algorithms on matrix manifolds
Hiroyuki Kasai, Pratik Kumar Jawanpuria, Bamdev Mishra

6:30 PM–9:00 PM | Pacific Ballroom (Poster #112)
Dead-ends and Secure Exploration in Reinforcement Learning
Mehdi Fatemi, Shikhar Sharma, Harm van Seijen, Samira Ebrahimi Kahou

6:30 PM–9:00 PM | Pacific Ballroom (Poster #195)
Orthogonal Random Forest for Causal Inference
Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

6:30 PM–9:00 PM | Pacific Ballroom (Poster #202)
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
Dheeraj Nagaraj, Prateek Jain, Praneeth Netrapalli

6:30 PM–9:00 PM | Pacific Ballroom (Poster #225)
Variational Implicit Processes
Chao Ma, Yingzhen Li, Jose Hernandez-Lobato

6:30 PM–9:00 PM | Pacific Ballroom (Poster #241)
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Ted Meeds, Geoffrey Roeder, Paul Grant, Andrew Phillips, Neil Dalchau

6:30 PM–9:00 PM | Pacific Ballroom (Poster #252)
Fast Context Adaptation via Meta-Learning
Luisa Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, Shimon Whiteson

6:30 PM–9:00 PM | Pacific Ballroom (Poster #262)
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
Kirthevasan Kandasamy, Willie Neiswanger, Reed Zhang, Akshay Krishnamurthy, Jeff Schneider, Barnabás Póczos

Thursday, June 13

9:20 AM–9:25 AM | Grand Ballroom (Oral)
Towards a Deep and Unified Understanding of Deep Neural Models in NLP
Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie

10:05 AM–10:10 AM | Room 201 (Oral)
Almost Unsupervised Text to Speech and Automatic Speech Recognition
Yi Ren, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu

10:15 AM–10:30 AM | Room 102 (Oral)
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
Alina Beygelzimer, David Pal, Balazs Szorenyi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang

11:25 AM–11:30 AM | Room 102 (Oral)
Adaptive Regret of Convex and Smooth Functions
Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou

11:30 AM–11:35 AM | Seaside Ballroom (Oral)
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
Alekh Agarwal, Miroslav Dudik, Zhiwei Steven Wu

11:35 AM–11:40 AM | Grand Ballroom (Oral)
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song

11:35 AM–11:40 AM | Hall B (Oral)
Non-Monotonic Sequential Text Generation
Sean Welleck, Kiante Brantley, Hal Daumé III, Kyunghyun Cho

12:00 PM–12:05 PM | Room 104 (Oral)
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu

12:05 PM–12:10 PM | Room 104 (Oral)
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
Limor Gultchin, Genevieve Patterson, Nancy Baym, Nathaniel Swinger, Adam Kalai

12:15 PM–12:20 PM | Hall B (Oral)
Efficient Training of BERT by Progressively Stacking
Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu

4:00 PM–4:20 PM | Hall B (Oral)
Decentralized Exploration in Multi-Armed Bandits
Raphael Feraud, Reda Alami, Romain Laroche

4:20 PM–4:25 PM | Hall A (Oral)
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
Ruo-Chun Tzeng, Shan-Hung (Brandon) Wu

4:20 PM–4:25 PM | Hall B (Oral)
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand Negahban

6:30 PM– 9:00 PM | Pacific Ballroom (Poster #22)
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
Ruo-Chun Tzeng, Shan-Hung (Brandon) Wu

6:30 PM–9:00 PM | Pacific Ballroom (Poster #45)
Non-Monotonic Sequential Text Generation
Sean Welleck, Kiante Brantley, Hal Daumé III, Kyunghyun Cho

6:30 PM–9:00 PM | Pacific Ballroom (Poster #50)
Efficient Training of BERT by Progressively Stacking
Linyuan Gong, Di He, Zhuohan Li, Tao Qin, Liwei Wang, Tie-Yan Liu

6:30 PM–9:00 PM | Pacific Ballroom (Poster #51)
Decentralized Exploration in Multi-Armed Bandits
Raphael Feraud, Reda Alami, Romain Laroche

6:30 PM–9:00 PM | Pacific Ballroom (Poster #52)
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand Negahban

6:30 PM–9:00 PM | Pacific Ballroom (Poster #62)
Towards a Deep and Unified Understanding of Deep Neural Models in NLP
Chaoyu Guan, Xiting Wang, Quanshi Zhang, Runjin Chen, Di He, Xing Xie

6:30 PM–9:00 PM | Pacific Ballroom (Poster #75)
A Convergence Theory for Deep Learning via Over-Parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, Zhao Song

6:30 PM–9:00 PM | Pacific Ballroom (Poster #107)
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu

6:30 PM–9:00 PM | Pacific Ballroom (Poster #108)
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
Limor Gultchin, Genevieve Patterson, Nancy Baym, Nathaniel Swinger, Adam Kalai

6:30 PM–9:00 PM | Pacific Ballroom (Poster #132)
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
Alekh Agarwal, Miroslav Dudik, Zhiwei Steven Wu

6:30 PM–9:00 PM | Pacific Ballroom (Poster #158)
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
Alina Beygelzimer, David Pal, Balazs Szorenyi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang

6:30 PM–9:00 PM | Pacific Ballroom (Poster #161)
Adaptive Regret of Convex and Smooth Functions
Lijun Zhang, Tie-Yan Liu, Zhi-Hua Zhou

6:30 PM–9:00 PM | Pacific Ballroom (Poster #224)
Almost Unsupervised Text to Speech and Automatic Speech Recognition
Yi Ren, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, Tie-Yan Liu

Friday, June 14

8:30 AM–6:00 PM | 104A (Workshop)
Climate Change: How Can AI Help?
Co-organizer: Jennifer Chayes

2:00 PM–6:00 PM | Seaside Ballroom (Workshop)
Real-world Sequential Decision Making: Reinforcement Learning and Beyond
Co-organizer: Adith Swaminathan

Saturday, June 15

8:30 AM–6:00 PM | 104B (Workshop)
AI For Social Good
Co-organizer: Lester Mackey

8:30 AM–6:00 PM | Seaside Ballroom (Workshop)
Adaptive and Multitask Learning: Algorithms & Systems
Co-organizer: Rich Caruana

8:30 AM–6:00 PM | 104A (Workshop)
Stein’s Method for Machine Learning and Statistics
Co-organizer: Lester Mackey

Career Opportunities






PhD students and recent graduates



Publications

Microsoft Research blog