Microsoft at WSDM 2021

About

Microsoft is proud to be a part of the 14th ACM Web Search and Data Mining Conference (WSDM 2021). Stop by our virtual booth to learn more about our research and open opportunities at Microsoft.

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Tuesday, March 9 Time (PST) Name
9:30 AM–10:00 AM Amy Siebenthaler, Recruiting
1:00 PM–2:00 PM Amy Siebenthaler, Recruiting
Wednesday, March 10 Time (PST) Name
9:30 AM–10:00 AM Amy Siebenthaler, Recruiting
1:00 PM–2:00 PM Amy Siebenthaler, Recruiting
Thursday, March 11 Time (PST) Name
4:00 AM–5:00 AM Royi Ronen, Principal Applied Research Manager

Program Chairs

Elad Yom-Tov​, General Chair
Noam Koenigstein, Poster and Demo Chair
Royi Ronen, Industry Day Chair

Senior Program Committee members

Paul Bennett, Nick Craswell, Bhaskar Mitra, Ahmed Hassan Awadallah, Ryen White, Emre Kiciman, Jake Hofman

Program Committee members

Fangzhao Wu, Adith Swaminathan, Wentao Wu, Mingjie Qian, Wei Wu, Xiaodong Liu, Manish Gupta, Daxin Jiang, Subhabrata Mukherjee, Arnd Christian König, Julia Kiseleva, Kuansan Wang, Hongwei Liang, Peter Bailey, Ning Gao, Xiaolu Lu

Sessions

*Times are in local Jerusalem time zone (GMT+2)

Tuesday, March 9

09:30 – 10:30 | Session 1: Society
Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
Jina Suh, Eric Horvitz, Ryen White, Tim Althoff

11:00 – 13:00 | Session 2: Classification
DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Kunal Dahiya, Deepak Saini, Anshul Mittal, Ankush Shaw, Kushal Dave, Akshay Soni, Himanshu Jain, Sumeet Agarwal, Manik Varma

11:00 – 13:00 | Session 2: Classification
DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal, Deepak Saini, Sumeet Agarwal, Manik Varma, Purushottam Kar

21:00 – 22:00 | Session 5: Experiments
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Emre Kiciman, Denis Charles, Joel Pfeiffer, Murat Bayir


22:00 – 24:00 | Posters 1 + Demos

[87] DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal, Deepak Saini, Sumeet Agarwal, Manik Varma, Purushottam Kar

[134] DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Kunal Dahiya, Deepak Saini, Anshul Mittal, Ankush Shaw, Kushal Dave, Akshay Soni, Himanshu Jain, Sumeet Agarwal, Manik Varma

[235] Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
Jina Suh, Eric Horvitz, Ryen White, Tim Althoff

[557] CalibreNet: Calibration Networks for Multilingual Sequence Labeling
Shining Liang, Linjun Shou, Jian Pei, Ming Gong, Wanli Zuo, Daxin Jiang

[583] HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam


Wednesday, March 10

8:30 – 9:30 | Keynote
Susan Dumais


13:00 – 15:00 | Posters 1 + Demos

[87] DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal, Deepak Saini, Sumeet Agarwal, Manik Varma, Purushottam Kar

[134] DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Kunal Dahiya, Deepak Saini, Anshul Mittal, Ankush Shaw, Kushal Dave, Akshay Soni, Himanshu Jain, Sumeet Agarwal, Manik Varma

[235] Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
Jina Suh, Eric Horvitz, Ryen White, Tim Althoff

[557] CalibreNet: Calibration Networks for Multilingual Sequence Labeling
Shining Liang, Linjun Shou, Jian Pei, Ming Gong, Wanli Zuo, Daxin Jiang

[583] HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam


20:00 – 21:00 | Keynote
Susan Dumais

21:00 – 22:00 | Session 10: Explainability and Intervention
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman


22:00 – 24:00 | Posters 2 + Demos

[305] Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman

[532] Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Emre Kiciman, Denis Charles, Joel Pfeiffer, Murat Bayir


Thursday, March 11

13:00 – 15:00 | Posters 2 + Demos

[305] Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan, Liz Manrao, Amit Sharma, Emre Kiciman

[532] Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Emre Kiciman, Denis Charles, Joel Pfeiffer, Murat Bayir

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