16 citations · 101 across the 22 of their papers we have counts for
25 papers
Expressivity and Statistical Trade-offs in Diffusion Policy Learning
Viet Vu, Renyuan Xu, Jiacheng Zhang +1
Diffusion-based policies have recently emerged as powerful policy parameterizations for reinforcement learning, representing state-conditioned action distributions as terminal laws…
Fast Policy Learning for Linear Quadratic Control with Entropy Regularization
Xin Guo, Xinyu Li, Renyuan Xu
This paper proposes and analyzes two new policy learning methods: regularized policy gradient (RPG) and iterative policy optimization (IPO), for a class of discounted linear-quadra…
Linear-quadratic Gaussian Games with Asymmetric Information: Belief Corrections Using the Opponents Actions
Ben Hambly, Renyuan Xu, Huining Yang
We consider two-player non-zero-sum linear-quadratic Gaussian games in which both players aim to minimize a quadratic cost function while controlling a linear and stochastic state…
Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Nonlinear control systems with partial information to the decision maker are prevalent in a variety of applications. As a step toward studying such nonlinear systems, this work exp…
Asymptotic Analysis of Deep Residual Networks
Rama Cont, Alain Rossier, Renyuan Xu
We investigate the asymptotic properties of deep Residual networks (ResNets) as the number of layers increases. We first show the existence of scaling regimes for trained weights m…
Risk-Aware Linear Bandits: Theory and Applications in Smart Order Routing
Jingwei Ji, Renyuan Xu, Ruihao Zhu
Motivated by practical considerations in machine learning for financial decision-making, such as risk aversion and large action space, we consider risk-aware bandits optimization w…
Convergence and Implicit Regularization Properties of Gradient Descent for Deep Residual Networks
Rama Cont, Alain Rossier, RenYuan Xu
We prove linear convergence of gradient descent to a global optimum for the training of deep residual networks with constant layer width and smooth activation function. We show tha…
Tail-GAN: Learning to Simulate Tail Risk Scenarios
Rama Cont, Mihai Cucuringu, Renyuan Xu +1
The estimation of loss distributions for dynamic portfolios requires the simulation of scenarios representing realistic joint dynamics of their components. We propose a novel data-…
Recent Advances in Reinforcement Learning in Finance
Ben Hambly, Renyuan Xu, Huining Yang
The rapid changes in the finance industry due to the increasing amount of data have revolutionized the techniques on data processing and data analysis and brought new theoretical a…
Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach
Haotian Gu, Xin Guo, Xiaoli Wei +1
One of the challenges for multi-agent reinforcement learning (MARL) is designing efficient learning algorithms for a large system in which each agent has only limited or partial in…
Policy Gradient Methods Find the Nash Equilibrium in N-player General-sum Linear-quadratic Games
Ben Hambly, Renyuan Xu, Huining Yang
We consider a general-sum N-player linear-quadratic game with stochastic dynamics over a finite horizon and prove the global convergence of the natural policy gradient method to th…
Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier +1
Residual networks (ResNets) have displayed impressive results in pattern recognition and, recently, have garnered considerable theoretical interest due to a perceived link with neu…
Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon
Ben Hambly, Renyuan Xu, Huining Yang
We explore reinforcement learning methods for finding the optimal policy in the linear quadratic regulator (LQR) problem. In particular, we consider the convergence of policy gradi…
Model-free Analysis of Dynamic Trading Strategies
Anna Ananova, Rama Cont, Renyuan Xu
We introduce a model-free approach for analyzing the risk and return for a broad class of dynamic trading strategies, including pairs trading, mean-reversion trading and other stat…
Entropy Regularization for Mean Field Games with Learning
Xin Guo, Renyuan Xu, Thaleia Zariphopoulou
Entropy regularization has been extensively adopted to improve the efficiency, the stability, and the convergence of algorithms in reinforcement learning. This paper analyzes both…
Interbank lending with benchmark rates: Pareto optima for a class of singular control games
Rama Cont, Xin Guo, Renyuan Xu
We analyze a class of stochastic differential games of singular control, motivated by the study of a dynamic model of interbank lending with benchmark rates. We describe Pareto opt…
Delay-Adaptive Learning in Generalized Linear Contextual Bandits
Jose Blanchet, Renyuan Xu, Zhengyuan Zhou
In this paper, we consider online learning in generalized linear contextual bandits where rewards are not immediately observed. Instead, rewards are available to the decision-maker…
A General Framework for Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu +1
This paper presents a general mean-field game (GMFG) framework for simultaneous learning and decision-making in stochastic games with a large population. It first establishes the e…
Mean-Field Controls with Q-learning for Cooperative MARL: Convergence and Complexity Analysis
Haotian Gu, Xin Guo, Xiaoli Wei +1
Multi-agent reinforcement learning (MARL), despite its popularity and empirical success, suffers from the curse of dimensionality. This paper builds the mathematical framework to a…
Dynamic Programming Principles for Mean-Field Controls with Learning
Haotian Gu, Xin Guo, Xiaoli Wei +1
Dynamic programming principle (DPP) is fundamental for control and optimization, including Markov decision problems (MDPs), reinforcement learning (RL), and more recently mean-fiel…
Transaction Cost Analytics for Corporate Bonds
Xin Guo, Charles-Albert Lehalle, Renyuan Xu
The electronic platform has been increasingly popular for executing large corporate bond orders by asset managers, who in turn have to assess the quality of their executions via Tr…
Learning Mean-Field Games
Xin Guo, Anran Hu, Renyuan Xu +1
This paper presents a general mean-field game (GMFG) framework for simultaneous learning and decision-making in stochastic games with a large population. It first establishes the e…
Consistency and Computation of Regularized MLEs for Multivariate Hawkes Processes
Xin Guo, Anran Hu, Renyuan Xu +1
This paper proves the consistency property for the regularized maximum likelihood estimators (MLEs) of multivariate Hawkes processes (MHPs). It also develops an alternating minimiz…
A class of stochastic games and moving free boundary problems
Xin Guo, Wenpin Tang, Renyuan Xu
In this paper we propose and analyze a class of -player stochastic games that include finite fuel stochastic games as a special case. We first derive sufficient conditions for t…