5 citations · 12 across the 8 of their papers we have counts for
8 papers
Adaptive Combinatorial Experimental Design: Pareto Optimality for Decision-Making and Inference
Hongrui Xie, Junyu Cao, Kan Xu
In this paper, we provide the first investigation into adaptive combinatorial experimental design, focusing on the trade-off between regret minimization and statistical power in co…
Stochastic Bandits with ReLU Neural Networks
Kan Xu, Hamsa Bastani, Surbhi Goel +1
We study the stochastic bandit problem with ReLU neural network structure. We show that a regret guarantee is achievable by considering bandits with one-layer…
Optimal Multitask Linear Regression and Contextual Bandits under Sparse Heterogeneity
Xinmeng Huang, Kan Xu, Donghwan Lee +3
Large and complex datasets are often collected from several, possibly heterogeneous sources. Multitask learning methods improve efficiency by leveraging commonalities across datase…
Multitask Learning and Bandits via Robust Statistics
Kan Xu, Hamsa Bastani
Decision-makers often simultaneously face many related but heterogeneous learning problems. For instance, a large retailer may wish to learn product demand at different stores to s…
Uniformly Conservative Exploration in Reinforcement Learning
Wanqiao Xu, Jason Yecheng Ma, Kan Xu +2
A key challenge to deploying reinforcement learning in practice is avoiding excessive (harmful) exploration in individual episodes. We propose a natural constraint on exploration -…
Robust Generalization of Quadratic Neural Networks via Function Identification
Kan Xu, Hamsa Bastani, Osbert Bastani
A key challenge facing deep learning is that neural networks are often not robust to shifts in the underlying data distribution. We study this problem from the perspective of the s…
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
Kan Xu, Xuanyi Zhao, Hamsa Bastani +1
Unstructured text provides decision-makers with a rich data source in many domains, ranging from product reviews in retail to nursing notes in healthcare. To leverage this informat…
Two-Stage Maximum Score Estimator
Wayne Yuan Gao, Sheng Xu, Kan Xu
This paper considers the asymptotic theory of a semiparametric M-estimator that is generally applicable to models that satisfy a monotonicity condition in one or several parametric…