Xiaoqi Liu — accepted AI-conference papers

2025

Non-stationary Bandit Convex Optimization: A Comprehensive Study

Xiaoqi Liu, Dorian Baudry, Julian Zimmert, Patrick Rebeschini, Arya Akhavan

NeurIPS 2025poster

Bandit Convex Optimization is a fundamental class of sequential decision-making problems, where the learner selects actions from a continuous domain and observes a loss (but not its gradient) at only one point per round. We study this problem in non-stationary environments, and aim to minimize the r…

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2024

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan

ICML 2024poster

We consider the problem of localizing change points in high-dimensional linear regression. We propose an Approximate Message Passing (AMP) algorithm for estimating both the signals and the change point locations. Assuming Gaussian covariates, we give an exact asymptotic characterization of its estim…

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