Huizhen Yu

Orcid: 0000-0002-3673-0094

According to our database1, Huizhen Yu authored at least 31 papers between 2001 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A Note on Stability in Asynchronous Stochastic Approximation without Communication Delays.
CoRR, 2023

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

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

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

Research on the Structural Impact of the Disappearance of China's Demographic Dividend on the Education Industry.
Proceedings of the ICETM 2020: 3rd International Conference on Education Technology Management, 2020

2018
On Generalized Bellman Equations and Temporal-Difference Learning.
J. Mach. Learn. Res., 2018

Two geometric input transformation methods for fast online reinforcement learning with neural nets.
CoRR, 2018

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

Multi-step Off-policy Learning Without Importance Sampling Ratios.
CoRR, 2017

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

Some Simulation Results for Emphatic Temporal-Difference Learning Algorithms.
CoRR, 2016

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

A Mixed Value and Policy Iteration Method for Stochastic Control with Universally Measurable Policies.
Math. Oper. Res., 2015

Emphatic Temporal-Difference Learning.
CoRR, 2015

On Convergence of Emphatic Temporal-Difference Learning.
Proceedings of The 28th Conference on Learning Theory, 2015

2013
On Boundedness of Q-Learning Iterates for Stochastic Shortest Path Problems.
Math. Oper. Res., 2013

Q-learning and policy iteration algorithms for stochastic shortest path problems.
Ann. Oper. Res., 2013

2012
Least Squares Temporal Difference Methods: An Analysis under General Conditions.
SIAM J. Control. Optim., 2012

Q-Learning and Enhanced Policy Iteration in Discounted Dynamic Programming.
Math. Oper. Res., 2012

2011
A Unifying Polyhedral Approximation Framework for Convex Optimization.
SIAM J. Optim., 2011

2010
Error Bounds for Approximations from Projected Linear Equations.
Math. Oper. Res., 2010

Convergence of Least Squares Temporal Difference Methods Under General Conditions.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Distributed asynchronous policy iteration in dynamic programming.
Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009
Convergence Results for Some Temporal Difference Methods Based on Least Squares.
IEEE Trans. Autom. Control., 2009

Basis function adaptation methods for cost approximation in MDP.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

2008
On Near Optimality of the Set of Finite-State Controllers for Average Cost POMDP.
Math. Oper. Res., 2008

New Error Bounds for Approximations from Projected Linear Equations.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

2006
Approximate solution methods for POMDP and POSMDP.
PhD thesis, 2006

2005
A Function Approximation Approach to Estimation of Policy Gradient for POMDP with Structured Policies.
Proceedings of the UAI '05, 2005

2004
Discretized Approximations for POMDP with Average Cost.
Proceedings of the UAI '04, 2004

2001
Combining Configurational and Statistical Approaches in Image Retrieval.
Proceedings of the Advances in Multimedia Information Processing, 2001


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