Harvineet Singh

According to our database, Harvineet Singh authored at least 26 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.

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 Gursoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo

CoRR, 2024

A hierarchical decomposition for explaining ML performance discrepancies.

Jean Feng, Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann

CoRR, 2024

2023

A Brief Tutorial on Sample Size Calculations for Fairness Audits.

Harvineet Singh, Fan Xia, Mi-Ok Kim, Romain Pirracchio, Rumi Chunara, Jean Feng

CoRR, 2023

Machine Learning for Health symposium 2023 - Findings track.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Thomas Hartvigsen, Harvineet Singh

CoRR, 2023

Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study.

Jean Feng, Adarsh Subbaswamy, Alexej Gossmann, Harvineet Singh, Berkman Sahiner, Mi-Ok Kim, Gene Pennello, Nicholas Petrick, Romain Pirracchio, Fan Xia

CoRR, 2023

Machine Learning for Health (ML4H) 2023.

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

Proceedings of the Machine Learning for Health, 2023

"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts.

Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi

Proceedings of the International Conference on Machine Learning, 2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Harvineet Singh, Matthäus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell

Proceedings of the International Conference on Machine Learning, 2023

Measures of Disparity and their Efficient Estimation.

Harvineet Singh, Rumi Chunara

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Data poisoning attacks on off-policy policy evaluation methods.

Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Machine Learning for Health (ML4H) 2022.

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

Proceedings of the Machine Learning for Health, 2022

Segmenting across places: The need for fair transfer learning with satellite imagery.

Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Towards Robust Off-Policy Evaluation via Human Inputs.

Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

Fair, Robust, and Data-Efficient Machine Learning in Healthcare.

Harvineet Singh

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

Learning Under Adversarial and Interventional Shifts.

Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju

CoRR, 2021

Fairness Violations and Mitigation under Covariate Shift.

Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020

An RNN-Survival Model to Decide Email Send Times.

Harvineet Singh, Moumita Sinha, Atanu R. Sinha, Sahil Garg, Neha Banerjee

CoRR, 2020

2019

Fair Predictors under Distribution Shift.

Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara

CoRR, 2019

Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts.

Aadhavan M. Nambhi, Bhanu Prakash Reddy, Aarsh Prakash Agarwal, Gaurav Verma, Harvineet Singh, Iftikhar Ahamath Burhanuddin

Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization, 2019

Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank.

Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Online Diverse Learning to Rank from Partial-Click Feedback.

Prakhar Gupta, Gaurush Hiranandani, Harvineet Singh, Branislav Kveton, Zheng Wen, Iftikhar Ahamath Burhanuddin

CoRR, 2018

Modeling Time to Open of Emails with a Latent State for User Engagement Level.

Moumita Sinha, Vishwa Vinay, Harvineet Singh

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Modeling Hint-Taking Behavior and Knowledge State of Students with Multi-Task Learning.

Harvineet Singh, Shiv Kumar Saini, Ritwick Chaudhry, Pradeep Dogga

Proceedings of the 11th International Conference on Educational Data Mining, 2018

2017

Learning User Representations in Online Social Networks using Temporal Dynamics of Information Diffusion.

Harvineet Singh, Amitabha Bagchi, Parag Singla

CoRR, 2017

Show and Recall: Learning What Makes Videos Memorable.

Sumit Shekhar, Dhruv Singal, Harvineet Singh, Manav Kedia, Akhil Shetty

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2015

On the role of conductance, geography and topology in predicting hashtag virality.

Siddharth Bora, Harvineet Singh, Anirban Sen, Amitabha Bagchi, Parag Singla

Soc. Netw. Anal. Min., 2015