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10/19/2022
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts
Performance of machine learning models may differ between training and d...
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09/18/2022
Towards Robust Off-Policy Evaluation via Human Inputs
Off-policy Evaluation (OPE) methods are crucial tools for evaluating pol...
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04/09/2022
Segmenting across places: The need for fair transfer learning with satellite imagery
The increasing availability of high-resolution satellite imagery has ena...
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03/29/2021
Learning Under Adversarial and Interventional Shifts
Machine learning models are often trained on data from one distribution ...
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04/21/2020
An RNN-Survival Model to Decide Email Send Times
Email communications are ubiquitous. Firms control send times of emails ...
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11/02/2019
Fair Predictors under Distribution Shift
Recent work on fair machine learning adds to a growing set of algorithmi...
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08/18/2019
Modeling Time to Open of Emails with a Latent State for User Engagement Level
Email messages have been an important mode of communication, not only fo...
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06/21/2019
Stuck? No worries!: Task-aware Command Recommendation and Proactive Help for Analysts
Data analytics software applications have become an integral part of the...
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11/01/2018
Online Diverse Learning to Rank from Partial-Click Feedback
Learning to rank is an important problem in machine learning and recomme...
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07/17/2017
