Harvineet Singh

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 33

Top Topics

Evaluation Method

Machine Learning Algorithms

Satellite Imagery

Top Venues

Publications

Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods. CoRR (2024)
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)
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 (2024)
Jean Feng, Harvineet Singh, Fan Xia, Adarsh Subbaswamy, Alexej Gossmann
A hierarchical decomposition for explaining ML performance discrepancies. CoRR (2024)
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 (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
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS (2023)
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 (2023)
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML (2023)
Harvineet Singh, Matthäus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell
When do Minimax-fair Learning and Empirical Risk Minimization Coincide? ICML (2023)
Harvineet Singh, Fan Xia, Mi-Ok Kim, Romain Pirracchio, Rumi Chunara, Jean Feng
A Brief Tutorial on Sample Size Calculations for Fairness Audits. CoRR (2023)
Harvineet Singh, Rumi Chunara
Measures of Disparity and their Efficient Estimation. AIES (2023)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Towards Robust Off-Policy Evaluation via Human Inputs. AIES (2022)
Harvineet Singh
Fair, Robust, and Data-Efficient Machine Learning in Healthcare. AIES (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 Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi
Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS (2022)
Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju
Data poisoning attacks on off-policy policy evaluation methods. UAI (2022)
Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara
Segmenting across places: The need for fair transfer learning with satellite imagery. CVPR Workshops (2022)
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR (2022)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Towards Robust Off-Policy Evaluation via Human Inputs. CoRR (2022)
Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara
Segmenting across places: The need for fair transfer learning with satellite imagery. CoRR (2022)
Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara
Fairness Violations and Mitigation under Covariate Shift. FAccT (2021)
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju
Learning Under Adversarial and Interventional Shifts. CoRR (2021)
Harvineet Singh, Moumita Sinha, Atanu R. Sinha, Sahil Garg, Neha Banerjee
An RNN-Survival Model to Decide Email Send Times. CoRR (2020)
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 (2019)
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)
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)
Moumita Sinha, Vishwa Vinay, Harvineet Singh
Modeling Time to Open of Emails with a Latent State for User Engagement Level. CoRR (2019)
Harvineet Singh, Rina Singh, Vishwali Mhasawade, Rumi Chunara
Fair Predictors under Distribution Shift. CoRR (2019)
Harvineet Singh, Shiv Kumar Saini, Ritwick Chaudhry, Pradeep Dogga
Modeling Hint-Taking Behavior and Knowledge State of Students with Multi-Task Learning. EDM (2018)
Prakhar Gupta, Gaurush Hiranandani, Harvineet Singh, Branislav Kveton, Zheng Wen, Iftikhar Ahamath Burhanuddin
Online Diverse Learning to Rank from Partial-Click Feedback. CoRR (2018)
Moumita Sinha, Vishwa Vinay, Harvineet Singh
Modeling Time to Open of Emails with a Latent State for User Engagement Level. WSDM (2018)
Sumit Shekhar, Dhruv Singal, Harvineet Singh, Manav Kedia, Akhil Shetty
Show and Recall: Learning What Makes Videos Memorable. CoRR (2017)
Harvineet Singh, Amitabha Bagchi, Parag Singla
Learning User Representations in Online Social Networks using Temporal Dynamics of Information Diffusion. CoRR (2017)
Sumit Shekhar, Dhruv Singal, Harvineet Singh, Manav Kedia, Akhil Shetty
Show and Recall: Learning What Makes Videos Memorable. ICCV Workshops (2017)
Siddharth Bora, Harvineet Singh, Anirban Sen, Amitabha Bagchi, Parag Singla
On the Role of Conductance, Geography and Topology in Predicting Hashtag Virality. CoRR (2015)
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) (2015)