Combining Configurational and Statistical Approaches in Image Retrieval. - Huizhen Yu; W. Eric L. Grimson (IEEE Pacific Rim Conference on Multimedia, 2001)

Discretized Approximations for POMDP with Average Cost. - Huizhen Yu; Dimitri P. Bertsekas (UAI, 2004)

A Function Approximation Approach to Estimation of Policy Gradient for POMDP with Structured Policies. - Huizhen Yu (UAI, 2005)

Approximate solution methods for POMDP and POSMDP. - Huizhen Yu (2006)

New Error Bounds for Approximations from Projected Linear Equations. - Huizhen Yu; Dimitri P. Bertsekas (EWRL, 2008)

Efficient Discriminative Training Method for Structured Predictions. - Huizhen Yu; Dimitri P. Bertsekas; Juho Rousu (MLG@ICML, 2008)

On Near Optimality of the Set of Finite-State Controllers for Average Cost POMDP. - Huizhen Yu; Dimitri P. Bertsekas (Math. Oper. Res., 2008)

Basis function adaptation methods for cost approximation in MDP. - Huizhen Yu; Dimitri P. Bertsekas (ADPRL, 2009)

Convergence Results for Some Temporal Difference Methods Based on Least Squares. - Huizhen Yu; Dimitri P. Bertsekas (IEEE Trans. Autom. Control., 2009)

Distributed asynchronous policy iteration in dynamic programming. - Dimitri P. Bertsekas; Huizhen Yu (Allerton, 2010)

Convergence of Least Squares Temporal Difference Methods Under General Conditions. - Huizhen Yu (ICML, 2010)

Error Bounds for Approximations from Projected Linear Equations. - Huizhen Yu; Dimitri P. Bertsekas (Math. Oper. Res., 2010)

A Unifying Polyhedral Approximation Framework for Convex Optimization. - Dimitri P. Bertsekas; Huizhen Yu (SIAM J. Optim., 2011)

Q-Learning and Enhanced Policy Iteration in Discounted Dynamic Programming. - Dimitri P. Bertsekas; Huizhen Yu (Math. Oper. Res., 2012)

Least Squares Temporal Difference Methods: An Analysis under General Conditions. - Huizhen Yu (SIAM J. Control. Optim., 2012)

Q-learning and policy iteration algorithms for stochastic shortest path problems. - Huizhen Yu; Dimitri P. Bertsekas (Ann. Oper. Res., 2013)

On Boundedness of Q-Learning Iterates for Stochastic Shortest Path Problems. - Huizhen Yu; Dimitri P. Bertsekas (Math. Oper. Res., 2013)

On Convergence of Emphatic Temporal-Difference Learning. - Huizhen Yu (COLT, 2015)

Emphatic Temporal-Difference Learning. - Ashique Rupam Mahmood; Huizhen Yu; Martha White; Richard S. Sutton (CoRR, 2015)

A Mixed Value and Policy Iteration Method for Stochastic Control with Universally Measurable Policies. - Huizhen Yu; Dimitri P. Bertsekas (Math. Oper. Res., 2015)

On Convergence of Value Iteration for a Class of Total Cost Markov Decision Processes. - Huizhen Yu (SIAM J. Control. Optim., 2015)

Some Simulation Results for Emphatic Temporal-Difference Learning Algorithms. - Huizhen Yu (CoRR, 2016)

Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize. - Huizhen Yu (J. Mach. Learn. Res., 2016)

Multi-step Off-policy Learning Without Importance Sampling Ratios. - Ashique Rupam Mahmood; Huizhen Yu; Richard S. Sutton (CoRR, 2017)

On Convergence of some Gradient-based Temporal-Differences Algorithms for Off-Policy Learning. - Huizhen Yu (CoRR, 2017)

Two geometric input transformation methods for fast online reinforcement learning with neural nets. - Sina Ghiassian; Huizhen Yu; Banafsheh Rafiee; Richard S. Sutton (CoRR, 2018)

On Generalized Bellman Equations and Temporal-Difference Learning. - Huizhen Yu; Ashique Rupam Mahmood; Richard S. Sutton (J. Mach. Learn. Res., 2018)

Research on the Structural Impact of the Disappearance of China's Demographic Dividend on the Education Industry. - Huizhen Yu (ICETM, 2020)

On the Minimum Pair Approach for Average Cost Markov Decision Processes with Countable Discrete Action Spaces and Strictly Unbounded Costs. - Huizhen Yu (SIAM J. Control. Optim., 2020)

Average Cost Optimality Inequality for Markov Decision Processes with Borel Spaces and Universally Measurable Policies. - Huizhen Yu (SIAM J. Control. Optim., 2020)

On Linear Programming for Constrained and Unconstrained Average-Cost Markov Decision Processes with Countable Action Spaces and Strictly Unbounded Costs. - Huizhen Yu (Math. Oper. Res., 2022)

A Note on Stability in Asynchronous Stochastic Approximation without Communication Delays. - Huizhen Yu; Yi Wan 004; Richard S. Sutton (CoRR, 2023)

On Convergence of Average-Reward Q-Learning in Weakly Communicating Markov Decision Processes. - Yi Wan 004; Huizhen Yu; Richard S. Sutton (CoRR, 2024)

Asynchronous Stochastic Approximation and Average-Reward Reinforcement Learning. - Huizhen Yu; Yi Wan 004; Richard S. Sutton (CoRR, 2024)

On Strategic Measures and Optimality Properties in Discrete-Time Stochastic Control with Universally Measurable Policies. - Huizhen Yu (Math. Oper. Res., 2024)