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2020 – today
- 2024
[c16]Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Anthony Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia:
Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens. CLeaR 2024: 587-608- [i18]Jean Feng, Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann:
A hierarchical decomposition for explaining ML performance discrepancies. CoRR abs/2402.14254 (2024) - [i17]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang
, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - [i16]Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju:
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods. CoRR abs/2404.04714 (2024) - 2023
- [c15]Harvineet Singh, Rumi Chunara:
Measures of Disparity and their Efficient Estimation. AIES 2023: 927-938 - [c14]Harvineet Singh, Matthäus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell:
When do Minimax-fair Learning and Empirical Risk Minimization Coincide? ICML 2023: 31969-31989 - [c13]Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi:
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML 2023: 41550-41578 - [c12]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen:
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS 2023: 1-12 - [e1]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Tom Hartvigsen, Harvineet Singh:
Machine Learning for Health, ML4H@NeurIPS 2023, 10 December 2023, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 225, PMLR 2023 [contents] - [i15]Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia:
Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study. CoRR abs/2311.11463 (2023) - [i14]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Thomas Hartvigsen, Harvineet Singh:
Machine Learning for Health symposium 2023 - Findings track. CoRR abs/2312.00655 (2023) - [i13]Harvineet Singh, Fan Xia, Mi-Ok Kim, Romain Pirracchio, Rumi Chunara, Jean Feng:
A Brief Tutorial on Sample Size Calculations for Fairness Audits. CoRR abs/2312.04745 (2023) - 2022
- [c11]Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju:
Towards Robust Off-Policy Evaluation via Human Inputs. AIES 2022: 686-699 - [c10]Harvineet Singh:
Fair, Robust, and Data-Efficient Machine Learning in Healthcare. AIES 2022: 914 - [c9]Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara:
Segmenting across places: The need for fair transfer learning with satellite imagery. CVPR Workshops 2022: 2915-2924 - [c8]Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi:
Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS 2022: 1-11 - [c7]Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju:
Data poisoning attacks on off-policy policy evaluation methods. UAI 2022: 1264-1274 - [i12]Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara:
Segmenting across places: The need for fair transfer learning with satellite imagery. CoRR abs/2204.04358 (2022) - [i11]Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju:
Towards Robust Off-Policy Evaluation via Human Inputs. CoRR abs/2209.08682 (2022) - [i10]Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi:
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR abs/2210.10769 (2022) - 2021
- [c6]Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara:
Fairness Violations and Mitigation under Covariate Shift. FAccT 2021: 3-13 - [i9]Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju:
Learning Under Adversarial and Interventional Shifts. CoRR abs/2103.15933 (2021) - 2020
- [i8]Harvineet Singh, Moumita Sinha, Atanu R. Sinha, Sahil Garg, Neha Banerjee:
An RNN-Survival Model to Decide Email Send Times. CoRR abs/2004.09900 (2020)
2010 – 2019
- 2019
- [c5]Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton:
Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank. UAI 2019: 722-732 - [c4]Aadhavan M. Nambhi, Bhanu Prakash Reddy, Aarsh Prakash Agarwal, Gaurav Verma, Harvineet Singh, Iftikhar Ahamath Burhanuddin:
Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts. UMAP 2019: 271-275 - [i7]Aadhavan M. Nambhi, Bhanu Prakash Reddy, Aarsh Prakash Agarwal, Gaurav Verma, Harvineet Singh, Iftikhar Ahamath Burhanuddin:
Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts. CoRR abs/1906.08973 (2019) - [i6]Moumita Sinha, Vishwa Vinay, Harvineet Singh:
Modeling Time to Open of Emails with a Latent State for User Engagement Level. CoRR abs/1908.06512 (2019) - [i5]Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara:
Fair Predictors under Distribution Shift. CoRR abs/1911.00677 (2019) - 2018
- [c3]Harvineet Singh, Shiv Kumar Saini, Ritwick Chaudhry, Pradeep Dogga:
Modeling Hint-Taking Behavior and Knowledge State of Students with Multi-Task Learning. EDM 2018 - [c2]Moumita Sinha, Vishwa Vinay, Harvineet Singh:
Modeling Time to Open of Emails with a Latent State for User Engagement Level. WSDM 2018: 531-539 - [i4]Prakhar Gupta, Gaurush Hiranandani, Harvineet Singh, Branislav Kveton, Zheng Wen, Iftikhar Ahamath Burhanuddin:
Online Diverse Learning to Rank from Partial-Click Feedback. CoRR abs/1811.00911 (2018) - 2017
- [c1]Sumit Shekhar, Dhruv Singal, Harvineet Singh, Manav Kedia, Akhil Shetty:
Show and Recall: Learning What Makes Videos Memorable. ICCV Workshops 2017: 2730-2739 - [i3]Sumit Shekhar, Dhruv Singal, Harvineet Singh, Manav Kedia, Akhil Shetty:
Show and Recall: Learning What Makes Videos Memorable. CoRR abs/1707.05357 (2017) - [i2]Harvineet Singh, Amitabha Bagchi, Parag Singla:
Learning User Representations in Online Social Networks using Temporal Dynamics of Information Diffusion. CoRR abs/1710.07622 (2017) - 2015
- [j1]Siddharth Bora, Harvineet Singh, Anirban Sen, Amitabha Bagchi, Parag Singla:
On the role of conductance, geography and topology in predicting hashtag virality. Soc. Netw. Anal. Min. 5(1): 57:1-57:15 (2015) - [i1]Siddharth Bora, Harvineet Singh, Anirban Sen, Amitabha Bagchi, Parag Singla:
On the Role of Conductance, Geography and Topology in Predicting Hashtag Virality. CoRR abs/1504.05351 (2015)
Coauthor Index
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