Zobrazeno 1 - 10
of 563
pro vyhledávání: '"Wainwright, P. J."'
Panel data consists of a collection of $N$ units that are observed over $T$ units of time. A policy or treatment is subject to staggered adoption if different units take on treatment at different times and remains treated (or never at all). Assessing
Externí odkaz:
http://arxiv.org/abs/2412.09482
Autor:
Xia, Eric, Wainwright, Martin J.
We study a class of prediction problems in which relatively few observations have associated responses, but all observations include both standard covariates as well as additional "helper" covariates. While the end goal is to make high-quality predic
Externí odkaz:
http://arxiv.org/abs/2412.09364
We provide a non-asymptotic analysis of the linear instrumental variable estimator allowing for the presence of exogeneous covariates. In addition, we introduce a novel measure of the strength of an instrument that can be used to derive non-asymptoti
Externí odkaz:
http://arxiv.org/abs/2410.02015
We study a class of structured Markov Decision Processes (MDPs) known as Exo-MDPs. They are characterized by a partition of the state space into two components: the exogenous states evolve stochastically in a manner not affected by the agent's action
Externí odkaz:
http://arxiv.org/abs/2409.14557
We study best-response type learning dynamics for two player zero-sum matrix games. We consider two settings that are distinguished by the type of information that each player has about the game and their opponent's strategy. The first setting is the
Externí odkaz:
http://arxiv.org/abs/2407.20128
Autor:
Yan, Yuling, Wainwright, Martin J.
Longitudinal or panel data can be represented as a matrix with rows indexed by units and columns indexed by time. We consider inferential questions associated with the missing data version of panel data induced by staggered adoption. We propose a com
Externí odkaz:
http://arxiv.org/abs/2401.13665
Autor:
Duan, Yaqi, Wainwright, Martin J.
We introduce a novel framework for analyzing reinforcement learning (RL) in continuous state-action spaces, and use it to prove fast rates of convergence in both off-line and on-line settings. Our analysis highlights two key stability properties, rel
Externí odkaz:
http://arxiv.org/abs/2401.05233
We study regression adjustment with general function class approximations for estimating the average treatment effect in the design-based setting. Standard regression adjustment involves bias due to sample re-use, and this bias leads to behavior that
Externí odkaz:
http://arxiv.org/abs/2311.10076
Key challenges in running a retail business include how to select products to present to consumers (the assortment problem), and how to price products (the pricing problem) to maximize revenue or profit. Instead of considering these problems in isola
Externí odkaz:
http://arxiv.org/abs/2309.08634
We study semi-parametric estimation of the population mean when data is observed missing at random (MAR) in the $n < p$ "inconsistency regime", in which neither the outcome model nor the propensity/missingness model can be estimated consistently. Con
Externí odkaz:
http://arxiv.org/abs/2309.01362