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04/10/2023
Regret Distribution in Stochastic Bandits: Optimal Trade-off between Expectation and Tail Risk
We study the trade-off between expectation and tail risk for regret dist...
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04/08/2023
Best Arm Identification with Fairness Constraints on Subpopulations
We formulate, analyze and solve the problem of best arm identification w...
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03/02/2023
Understanding plasticity in neural networks
Plasticity, the ability of a neural network to quickly change its predic...
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11/26/2022
Efficient Targeted Learning of Heterogeneous Treatment Effects for Multiple Subgroups
In biomedical science, analyzing treatment effect heterogeneity plays an...
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10/13/2022
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations
We study a game between liquidity provider and liquidity taker agents in...
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10/13/2022
Adaptive A/B Tests and Simultaneous Treatment Parameter Optimization
Constructing asymptotically valid confidence intervals through a valid c...
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09/12/2022
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization
Nonsmooth nonconvex optimization problems broadly emerge in machine lear...
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06/23/2022
Inference on the Best Policies with Many Covariates
Understanding the impact of the most effective policies or treatments on...
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06/07/2022
A Simple and Optimal Policy Design with Safety against Heavy-tailed Risk for Multi-armed Bandits
We design new policies that ensure both worst-case optimality for expect...
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02/08/2022
GrASP: Gradient-Based Affordance Selection for Planning
Planning with a learned model is arguably a key component of intelligenc...
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01/09/2022
Selecting the Best Optimizing System
We formulate selecting the best optimizing system (SBOS) problems and pr...
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06/28/2021
Dynamic Planning and Learning under Recovering Rewards
Motivated by emerging applications such as live-streaming e-commerce, pr...
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03/27/2021
Continuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization
Conditional Generative Adversarial Networks are known to be difficult to...
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02/09/2021
Pairwise Weights for Temporal Credit Assignment
How much credit (or blame) should an action taken in a state get for a f...
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02/09/2021
Learning State Representations from Random Deep Action-conditional Predictions
In this work, we study auxiliary prediction tasks defined by temporal-di...
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12/27/2020
Doubly Stochastic Generative Arrivals Modeling
We propose a new framework named DS-WGAN that integrates the doubly stoc...
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06/22/2020
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
Optimal transport (OT) distances are increasingly used as loss functions...
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06/21/2020
Automated Optical Multi-layer Design via Deep Reinforcement Learning
Optical multi-layer thin films are widely used in optical and energy app...
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12/11/2019
What Can Learned Intrinsic Rewards Capture?
Reinforcement learning agents can include different components, such as ...
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05/13/2019
Ques-Chain: an Ethereum Based E-Voting System
Ethereum is an open-source, public, blockchain-based distributed computi...
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04/17/2018
On Learning Intrinsic Rewards for Policy Gradient Methods
In many sequential decision making tasks, it is challenging to design re...
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06/11/2017
