conftrace_

stochastic approximation

101 papers

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SA

Co-occurring keywords

convergence rate (607) reinforcement learning (4352) temporal difference learning (149) markov chain (207) finite-time analysis (31) convergence analysis (395) markov decision process (790) convex optimization (1321) online learning (1777) policy evaluation (115)

Papers

Asymptotic and Finite Sample Analysis of Nonexpansive Stochastic Approximations with Markovian Noise AAAI 2026
GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Bandits AAAI 2026
The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise JMLR 2025
EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback JMLR 2025
Convergence Rate in a Nonlinear Two-Time-Scale Stochastic Approximation with State (Time)-Dependence AAAI 2025
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise NIPS 2024
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization NIPS 2024
Periodic agent-state based Q-learning for POMDPs NIPS 2024
Finite-Time Convergence Rates of Decentralized Local Markovian Stochastic Approximation IJCAI 2024
Stochastic Approximation with Biased MCMC for Expectation Maximization AISTATS 2024
An Analysis of Quantile Temporal-Difference Learning JMLR 2024
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024
FastMAC: Stochastic Spectral Sampling of Correspondence Graph CVPR 2024
Random Function Descent NIPS 2024
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality JMLR 2024
Oja's Algorithm for Streaming Sparse PCA NIPS 2024
Zeroth-order Stochastic Approximation Algorithms for DR-submodular Optimization JMLR 2024
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize NIPS 2024
Random Smoothing Regularization in Kernel Gradient Descent Learning JMLR 2024
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability COLT 2024
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation JMLR 2023
Top-k data selection via distributed sample quantile inference L4DC 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation NIPS 2023
Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start JMLR 2023
Stochastic Approximation Algorithms for Systems of Interacting Particles NIPS 2023