Harvineet Singh

Orcid: 0000-0003-0166-9331

According to our database1, Harvineet Singh authored at least 27 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.
CoRR, 2024

A hierarchical decomposition for explaining ML performance discrepancies.
CoRR, 2024

Designing monitoring strategies for deployed machine learning algorithms: navigating performativity through a causal lens.
Proceedings of the Causal Learning and Reasoning, 2024

2023
A Brief Tutorial on Sample Size Calculations for Fairness Audits.
CoRR, 2023

Machine Learning for Health symposium 2023 - Findings track.
CoRR, 2023

Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study.
CoRR, 2023


"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts.
Proceedings of the International Conference on Machine Learning, 2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?
Proceedings of the International Conference on Machine Learning, 2023

Measures of Disparity and their Efficient Estimation.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022
Data poisoning attacks on off-policy policy evaluation methods.
Proceedings of the Uncertainty in Artificial Intelligence, 2022


Segmenting across places: The need for fair transfer learning with satellite imagery.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Towards Robust Off-Policy Evaluation via Human Inputs.
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.
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.
CoRR, 2021

Fairness Violations and Mitigation under Covariate Shift.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

2020
An RNN-Survival Model to Decide Email Send Times.
CoRR, 2020

2019
Fair Predictors under Distribution Shift.
CoRR, 2019

Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts.
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.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018
Online Diverse Learning to Rank from Partial-Click Feedback.
CoRR, 2018

Modeling Time to Open of Emails with a Latent State for User Engagement Level.
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.
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.
CoRR, 2017

Show and Recall: Learning What Makes Videos Memorable.
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.
Soc. Netw. Anal. Min., 2015


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