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

Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning COLT 2018
Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation NIPS 2018
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions NIPS 2018
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing JMLR 2018
Online Learning with Transductive Regret NIPS 2017
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data NIPS 2017
Stochastic Approximation for Canonical Correlation Analysis NIPS 2017
Stochastic Submodular Maximization: The Case of Coverage Functions NIPS 2017
Zap Q-Learning NIPS 2017
Scalable Gaussian Process Classification via Expectation Propagation AISTATS 2016
Stochastic Discrete Clenshaw-Curtis Quadrature ICML 2016
Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize JMLR 2016
Large-scale log-determinant computation through stochastic Chebyshev expansions ICML 2015
The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling ICML 2015
Towards Maximum Likelihood: Learning Undirected Graphical Models using Persistent Sequential Monte Carlo ACML 2014
Universal Option Models NIPS 2014
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NIPS 2013
Adaptive Metropolis with Online Relabeling AISTATS 2012
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NIPS 2011
Approximation of hidden Markov models by mixtures of experts with application to particle filtering AISTATS 2010
Online Learning for Matrix Factorization and Sparse Coding JMLR 2010
Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition NIPS 2010
A Stochastic approximation method for inference in probabilistic graphical models NIPS 2009
Learning in Markov Random Fields using Tempered Transitions NIPS 2009
An interior-point stochastic approximation method and an L1-regularized delta rule NIPS 2008