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06/22/2023
Pure Exploration in Bandits with Linear Constraints
We address the problem of identifying the optimal policy with a fixed co...
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03/16/2023
Unsupervised domain adaptation by learning using privileged information
Successful unsupervised domain adaptation (UDA) is guaranteed only under...
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03/15/2023
Practicality of generalization guarantees for unsupervised domain adaptation with neural networks
Understanding generalization is crucial to confidently engineer and depl...
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09/15/2022
Efficient learning of nonlinear prediction models with time-series privileged information
In domains where sample sizes are limited, efficient learning algorithms...
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11/22/2021
Case-based off-policy policy evaluation using prototype learning
Importance sampling (IS) is often used to perform off-policy policy eval...
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11/12/2021
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects
Simulators make unique benchmarks for causal effect estimation since the...
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10/28/2021
Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models
We study prediction of future outcomes with supervised models that use p...
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09/06/2021
Thompson Sampling for Bandits with Clustered Arms
We propose algorithms based on a multi-level Thompson sampling scheme, f...
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05/28/2021
Learning Approximate and Exact Numeral Systems via Reinforcement Learning
Recent work (Xu et al., 2020) has suggested that numeral systems in diff...
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07/02/2020
Learning to search efficiently for causally near-optimal treatments
Finding an effective medical treatment often requires a search by trial ...
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01/21/2020
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
Practitioners in diverse fields such as healthcare, economics and educat...
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10/10/2019
Estimation of Utility-Maximizing Bounds on Potential Outcomes
Estimation of individual treatment effects is often used as the basis fo...
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07/09/2019
Characterization of Overlap in Observational Studies
Overlap between treatment groups is required for nonparametric estimatio...
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03/28/2019
A Survey on Graph Kernels
Graph kernels have become an established and widely-used technique for s...
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03/08/2019
Support and Invertibility in Domain-Invariant Representations
Learning domain-invariant representations has become a popular approach ...
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11/14/2018
Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions
We study heterogeneity in the effect of a mindset intervention on studen...
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05/30/2018
Why Is My Classifier Discriminatory?
Recent attempts to achieve fairness in predictive models focus on the ba...
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02/23/2018
Learning Weighted Representations for Generalization Across Designs
Predictive models that generalize well under distributional shift are of...
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11/10/2016
Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence
Acquiring your first language is an incredible feat and not easily dupli...
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06/13/2016
Estimating individual treatment effect: generalization bounds and algorithms
There is intense interest in applying machine learning to problems of ca...
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05/12/2016