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function approximation

319 papers

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Co-occurring keywords

reinforcement learning (4122) regret bound (1918) markov decision process (788) sample complexity (1158) neural network (6616) temporal difference learning (149) value function (294) offline reinforcement learning (492) deep reinforcement learning (903) value iteration (162)

Papers

Streaming Generated Gaussian Process Experts for Online Learning and Control AAAI 2026
Quantum Non-Linear Bandit Optimization AAAI 2026
Physics Informed Kolmogorov-Arnold Neural Networks for Dynamical Analysis via Efficient-KAN and WAV-KAN JMLR 2025
Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions AAAI 2025
On Evaluating LLMs’ Capabilities as Functional Approximators: A Bayesian Evaluation Framework COLING 2025
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise JMLR 2025
X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning IJCAI 2025
Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs AAAI 2025
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation JMLR 2025
Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation AAAI 2025
Finite-Time Analysis of Heterogeneous Federated Temporal Difference Learning IJCAI 2025
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs NIPS 2024
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NIPS 2024
Prior-dependent analysis of posterior sampling reinforcement learning with function approximation AISTATS 2024
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation NIPS 2024
Offline Primal-Dual Reinforcement Learning for Linear MDPs AISTATS 2024
Learning to Understand: Identifying Interactions via the Möbius Transform NIPS 2024
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation NIPS 2024
Policy Mirror Descent with Lookahead NIPS 2024
Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NIPS 2024
How Does Variance Shape the Regret in Contextual Bandits? NIPS 2024
Recurrent Reinforcement Learning with Memoroids NIPS 2024
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn NIPS 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NIPS 2024
A Doubly Robust Approach to Sparse Reinforcement Learning AISTATS 2024