39 citations · 63 across the 12 of their papers we have counts for
13 papers
Data Poisoning Attacks on Off-Policy Policy Evaluation Methods
Elita Lobo, Harvineet Singh, Marek Petrik +2
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expen…
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts
Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi +1
Machine learning models frequently experience performance drops under distribution shifts. The underlying cause of such shifts may be multiple simultaneous factors such as changes…
Towards Robust Off-Policy Evaluation via Human Inputs
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez +1
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or…
Segmenting across places: The need for fair transfer learning with satellite imagery
Miao Zhang, Harvineet Singh, Lazarus Chok +1
The increasing availability of high-resolution satellite imagery has enabled the use of machine learning to support land-cover measurement and inform policy-making. However, labell…
Learning Under Adversarial and Interventional Shifts
Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez +1
Machine learning models are often trained on data from one distribution and deployed on others. So it becomes important to design models that are robust to distribution shifts. Mos…
An RNN-Survival Model to Decide Email Send Times
Harvineet Singh, Moumita Sinha, Atanu R. Sinha +2
Email communications are ubiquitous. Firms control send times of emails and thereby the instants at which emails reach recipients (it is assumed email is received instantaneously f…
Fairness Violations and Mitigation under Covariate Shift
Harvineet Singh, Rina Singh, Vishwali Mhasawade +1
We study the problem of learning fair prediction models for unseen test sets distributed differently from the train set. Stability against changes in data distribution is an import…
Modeling Time to Open of Emails with a Latent State for User Engagement Level
Moumita Sinha, Vishwa Vinay, Harvineet Singh
Email messages have been an important mode of communication, not only for work, but also for social interactions and marketing. When messages have time sensitive information, it be…
Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts
Aadhavan M. Nambhi, Bhanu Prakash Reddy, Aarsh Prakash Agarwal +3
Data analytics software applications have become an integral part of the decision-making process of analysts. Users of such a software face challenges due to insufficient product a…
Online Diverse Learning to Rank from Partial-Click Feedback
Prakhar Gupta, Gaurush Hiranandani, Harvineet Singh +3
Learning to rank is an important problem in machine learning and recommender systems. In a recommender system, a user is typically recommended a list of items. Since the user is un…
Learning User Representations in Online Social Networks using Temporal Dynamics of Information Diffusion
Harvineet Singh, Amitabha Bagchi, Parag Singla
This article presents a novel approach for learning low-dimensional distributed representations of users in online social networks. Existing methods rely on the network structure f…
Show and Recall: Learning What Makes Videos Memorable
Sumit Shekhar, Dhruv Singal, Harvineet Singh +2
With the explosion of video content on the Internet, there is a need for research on methods for video analysis which take human cognition into account. One such cognitive measure…
On the Role of Conductance, Geography and Topology in Predicting Hashtag Virality
Siddharth Bora, Harvineet Singh, Anirban Sen +2
We focus on three aspects of the early spread of a hashtag in order to predict whether it will go viral: the network properties of the subset of users tweeting the hashtag, its geo…