*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 (opens in new tab), Eric Horvitz (opens in new tab), Ryen White (opens in new tab), 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 (opens in new tab), Anshul Mittal, Ankush Shaw, Kushal Dave (opens in new tab), Akshay Soni (opens in new tab), Himanshu Jain, Sumeet Agarwal, Manik Varma (opens in new tab)
11:00 – 13:00 | Session 2: Classification
DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal (opens in new tab), Deepak Saini (opens in new tab), Sumeet Agarwal, Manik Varma (opens in new tab), Purushottam Kar (opens in new tab)
21:00 – 22:00 | Session 5: Experiments
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Emre Kiciman (opens in new tab), Denis Charles (opens in new tab), 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 (opens in new tab), Deepak Saini (opens in new tab), Sumeet Agarwal, Manik Varma (opens in new tab), Purushottam Kar (opens in new tab)
[134] DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Kunal Dahiya, Deepak Saini (opens in new tab), Anshul Mittal, Ankush Shaw, Kushal Dave (opens in new tab), Akshay Soni (opens in new tab), Himanshu Jain, Sumeet Agarwal, Manik Varma (opens in new tab)
[235] Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
Jina Suh (opens in new tab), Eric Horvitz (opens in new tab), Ryen White (opens in new tab), Tim Althoff
[557] CalibreNet: Calibration Networks for Multilingual Sequence Labeling
Shining Liang, Linjun Shou (opens in new tab), Jian Pei, Ming Gong (opens in new tab), Wanli Zuo, Daxin Jiang (opens in new tab)
[583] HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
Rahul Ragesh (opens in new tab), Sundararajan Sellamanickam (opens in new tab), Arun Iyer (opens in new tab), Ramakrishna Bairi, Vijay Lingam (opens in new tab)
Wednesday, March 10
8:30 – 9:30 | Keynote
Susan Dumais (opens in new tab)
13:00 – 15:00 | Posters 1 + Demos
[87] DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal (opens in new tab), Deepak Saini (opens in new tab), Sumeet Agarwal, Manik Varma (opens in new tab), Purushottam Kar (opens in new tab)
[134] DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents
Kunal Dahiya, Deepak Saini (opens in new tab), Anshul Mittal, Ankush Shaw, Kushal Dave (opens in new tab), Akshay Soni (opens in new tab), Himanshu Jain, Sumeet Agarwal, Manik Varma (opens in new tab)
[235] Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications
Jina Suh (opens in new tab), Eric Horvitz (opens in new tab), Ryen White (opens in new tab), Tim Althoff
[557] CalibreNet: Calibration Networks for Multilingual Sequence Labeling
Shining Liang, Linjun Shou (opens in new tab), Jian Pei, Ming Gong (opens in new tab), Wanli Zuo, Daxin Jiang (opens in new tab)
[583] HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification
Rahul Ragesh (opens in new tab), Sundararajan Sellamanickam (opens in new tab), Arun Iyer (opens in new tab), Ramakrishna Bairi, Vijay Lingam (opens in new tab)
20:00 – 21:00 | Keynote
Susan Dumais (opens in new tab)
21:00 – 22:00 | Session 10: Explainability and Intervention
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan (opens in new tab), Liz Manrao (opens in new tab), Amit Sharma (opens in new tab), Emre Kiciman (opens in new tab)
22:00 – 24:00 | Posters 2 + Demos
[305] Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions
Yanbo Xu, Divyat Mahajan (opens in new tab), Liz Manrao (opens in new tab), Amit Sharma (opens in new tab), Emre Kiciman (opens in new tab)
[532] Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Emre Kiciman (opens in new tab), Denis Charles (opens in new tab), 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 (opens in new tab), Liz Manrao (opens in new tab), Amit Sharma (opens in new tab), Emre Kiciman (opens in new tab)
[532] Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction
Shuxi Zeng, Emre Kiciman (opens in new tab), Denis Charles (opens in new tab), Joel Pfeiffer, Murat Bayir