function approximation

Black-Box Methods for Restoring Monotonicity ICML 2020 Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions ICML 2020 Count-Based Exploration with the Successor Representation AAAI 2020 Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis NeurIPS 2020 Differential Equation Units: Learning Functional Forms of Activation Functions from Data AAAI 2020 Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020 Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning AAAI 2020 Frequentist Regret Bounds for Randomized Least-Squares Value Iteration AISTATS 2020 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values ICML 2020 Learning Near Optimal Policies with Low Inherent Bellman Error ICML 2020 Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium COLT 2020 Maximum-and-Concatenation Networks ICML 2020 Nonlinear System Identification via Tensor Completion AAAI 2020 On Simulation and Trajectory Prediction with Gaussian Process Dynamics L4DC 2020 On the Modularity of Hypernetworks NeurIPS 2020 On the Role of Weight Sharing During Deep Option Learning AAAI 2020 Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes COLT 2020 Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation ICML 2020 Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations NeurIPS 2020 Rational neural networks NeurIPS 2020 Representations for Stable Off-Policy Reinforcement Learning ICML 2020 Residual Neural Processes AAAI 2020 Root-n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank COLT 2020 Sparse Shrunk Additive Models ICML 2020 The phase diagram of approximation rates for deep neural networks NeurIPS 2020