11 citations · 27 across the 15 of their papers we have counts for
6 papers · 1 filter
Policy Optimization and Statistical Inference for Online Contextual Matrix Games
Liner Xiang, Yixin Wang, Hengrui Cai
Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for example, hotels must account fo…
On the Identifiability of Switching Dynamical Systems
Carles Balsells-Rodas, Yixin Wang, Yingzhen Li
The identifiability of latent variable models has received increasing attention due to its relevance in interpretability and out-of-distribution generalisation. In this work, we st…
Offline Policy Evaluation and Optimization under Confounding
Chinmaya Kausik, Yangyi Lu, Kevin Tan +3
Evaluating and optimizing policies in the presence of unobserved confounders is a problem of growing interest in offline reinforcement learning. Using conventional methods for offl…
Interventional Causal Representation Learning
Kartik Ahuja, Divyat Mahajan, Yixin Wang +1
Causal representation learning seeks to extract high-level latent factors from low-level sensory data. Most existing methods rely on observational data and structural assumptions (…
Anticipating Performativity by Predicting from Predictions
Celestine Mendler-Dünner, Frances Ding, Yixin Wang
Predictions about people, such as their expected educational achievement or their credit risk, can be performative and shape the outcome that they aim to predict. Understanding the…
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection
Kush Bhatia, Nikki Lijing Kuang, Yi-An Ma +1
Variational inference has recently emerged as a popular alternative to the classical Markov chain Monte Carlo (MCMC) in large-scale Bayesian inference. The core idea is to trade st…