conftrace_

value function approximation

100 papers

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Also known as

VFA

Co-occurring keywords

reinforcement learning (4352) value function (295) markov decision process (790) policy iteration (99) off-policy learning (228) temporal difference learning (149) deep reinforcement learning (903) regret bound (1926) representation learning (6206) approximate dynamic programming (31)

Papers

Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks AAAI 2021
State-Aware Value Function Approximation with Attention Mechanism for Restless Multi-armed Bandits IJCAI 2021
Adaptive Approximate Policy Iteration AISTATS 2021
Boosting Offline Reinforcement Learning with Residual Generative Modeling IJCAI 2021
Risk-Averse Learning by Temporal Difference Methods with Markov Risk Measures JMLR 2021
Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning ICML 2021
Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021
Batch Value-function Approximation with Only Realizability ICML 2021
Temporal Difference Learning as Gradient Splitting ICML 2021
Near-Optimal Representation Learning for Linear Bandits and Linear RL ICML 2021
Generalizable Episodic Memory for Deep Reinforcement Learning ICML 2021
Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes RSS 2020
ConQUR: Mitigating Delusional Bias in Deep Q-Learning ICML 2020
Breaking the Curse of Many Agents: Provable Mean Embedding Q-Iteration for Mean-Field Reinforcement Learning ICML 2020
Uncorrected Least-Squares Temporal Difference with Lambda-Return AAAI 2020
Deep Neural Network Approximated Dynamic Programming for Combinatorial Optimization AAAI 2020
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension NIPS 2020
Critic Regularized Regression NIPS 2020
Model-Based Reinforcement Learning with Value-Targeted Regression L4DC 2020
Finite-sample Analysis of Greedy-GQ with Linear Function Approximation under Markovian Noise UAI 2020
Towards Better Interpretability in Deep Q-Networks AAAI 2019
A Comparative Analysis of Expected and Distributional Reinforcement Learning AAAI 2019
Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing AAAI 2019
Information-Theoretic Considerations in Batch Reinforcement Learning ICML 2019
Solving Partially Observable Stochastic Games with Public Observations AAAI 2019