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02/15/2023
Optimal Sample Complexity of Reinforcement Learning for Uniformly Ergodic Discounted Markov Decision Processes
We consider the optimal sample complexity theory of tabular reinforcemen...
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03/14/2022
The Design and Implementation of a Broadly Applicable Algorithm for Optimizing Intra-Day Surgical Scheduling
Surgical scheduling optimization is an active area of research. However,...
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02/13/2022
Surgical Scheduling via Optimization and Machine Learning with Long-Tailed Data
Using data from cardiovascular surgery patients with long and highly var...
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05/11/2021
Frank-Wolfe Methods in Probability Space
We introduce a new class of Frank-Wolfe algorithms for minimizing differ...
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11/18/2020
The Development and Deployment of a Model for Hospital-level COVID-19 Associated Patient Demand Intervals from Consistent Estimators (DICE)
Hospitals commonly project demand for their services by combining their ...
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06/10/2020
Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood Approach
Suppose an online platform wants to compare a treatment and control poli...
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08/24/2019
Optimal best arm selection for general distributions
Given a finite set of unknown distributions or arms that can be sampled ...
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06/07/2019
Optimal Transport Relaxations with Application to Wasserstein GANs
We propose a family of relaxations of the optimal transport problem whic...
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01/30/2019
Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
The goal of this paper is to provide a unifying view of a wide range of ...
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05/05/2018
An Accelerated Approach to Safely and Efficiently Test Pre-produced Autonomous Vehicles on Public Streets
Various automobile and mobility companies, for instance, Ford, Uber, and...
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04/04/2018
A Fixed Point Theorem for Iterative Random Contraction Operators over Banach Spaces
Consider a contraction operator T over a Banach space X with a fixed po...
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10/11/2016