function approximation

Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation ICLR 2025 The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise JMLR 2025 Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation AAAI 2025 X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning IJCAI 2025 Achieving Constant Regret in Linear Markov Decision Processes NeurIPS 2024 ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints ICML 2024 Adaptive Order Q-learning IJCAI 2024 Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning NeurIPS 2024 A Doubly Robust Approach to Sparse Reinforcement Learning AISTATS 2024 Alias-Free Mamba Neural Operator NeurIPS 2024 A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation NeurIPS 2024 A Primal-Dual-Critic Algorithm for Offline Constrained Reinforcement Learning AISTATS 2024 Batch normalization is sufficient for universal function approximation in CNNs ICLR 2024 Function Based Sim-to-Real Learning for Shape Control of Deformable Free-form Surfaces RSS 2024 Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024 How Does Variance Shape the Regret in Contextual Bandits? NeurIPS 2024 Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn NeurIPS 2024 Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NeurIPS 2024 Learning Social Welfare Functions NeurIPS 2024 Learning to Understand: Identifying Interactions via the Möbius Transform NeurIPS 2024 Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs NeurIPS 2024 Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NeurIPS 2024 Neural Network Approximation for Pessimistic Offline Reinforcement Learning AAAI 2024 Offline Primal-Dual Reinforcement Learning for Linear MDPs AISTATS 2024 On learning history-based policies for controlling Markov decision processes AISTATS 2024