1 citations · 1 across the 9 of their papers we have counts for
9 papers
Gaussian Approximation in Wasserstein-p: Markovian Martingale Differences and Stochastic Approximation
Yixuan Zhang, Qiaomin Xie
We establish nonasymptotic Gaussian approximation bounds in higher-order Wasserstein distance , , for deterministic matrix-weighted sums of multivariate Poisson martin…
On the Peril of (Even a Little) Nonstationarity in Satisficing Regret Minimization
Yixuan Zhang, Ruihao Zhu, Qiaomin Xie
Motivated by the principle of satisficing in decision-making, we study satisficing regret guarantees for nonstationary -armed bandits. We show that in the general realizable, pi…
Optimization with Parametric Variational Inequality Constraints on a Moving Set Based on a Smoothing Method
Xiaojun Chen, Jin Zhang, Yixuan Zhang
This paper focuses on optimization problems constrained by Parametric Variational Inequalities (PVI) defined on a moving set. Unlike most existing works on mathematical programs wi…
Wasserstein-p Central Limit Theorem Rates: From Local Dependence to Markov Chains
Yixuan Zhang, Qiaomin Xie
Non-asymptotic central limit theorem (CLT) rates play a central role in modern machine learning and operations research. In this paper, we study CLT rates for multivariate dependen…
Contextual Online Pricing with (Biased) Offline Data
Yixuan Zhang, Ruihao Zhu, Qiaomin Xie
We study contextual online pricing with biased offline data. For the scalar price elasticity case, we identify the instance-dependent quantity that measures how far the offli…
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
Yixuan Zhang, Dongyan Huo, Yudong Chen +1
Motivated by robust and quantile regression problems, we investigate the stochastic gradient descent (SGD) algorithm for minimizing an objective function that is locally strong…
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
Dongyan Huo, Yixuan Zhang, Yudong Chen +1
In this work, we investigate stochastic approximation (SA) with Markovian data and nonlinear updates under constant stepsize . Existing work has primarily focused on either i.…
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA
Yixuan Zhang, Dongyan Huo, Yudong Chen +1
Motivated by Q-learning, we study nonsmooth contractive stochastic approximation (SA) with constant stepsize. We focus on two important classes of dynamics: 1) nonsmooth contractiv…
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation
Yixuan Zhang, Qiaomin Xie
Stochastic Approximation (SA) is a widely used algorithmic approach in various fields, including optimization and reinforcement learning (RL). Among RL algorithms, Q-learning is pa…