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Stochastic approximation
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#	Item
61	An Adaptive Learning Rate for Stochastic Variational Inference Rajesh Ranganath Princeton University, 35 Olden St., Princeton, NJ[removed]RAJESHR @ CS . PRINCETON . EDU Add to Reading List Source URL: www.cs.columbia.edu Language: English - Date: 2015-03-12 00:16:22 Stochastic optimization Probability theory Stochastic approximation Mathematical optimization Bayesian inference Latent Dirichlet allocation Expectation–maximization algorithm Variational Bayesian methods Statistics Bayesian statistics Estimation theory
62	c 2009 Society for Industrial and Applied Mathematics SIAM J. OPTIM. Vol. 19, No. 4, pp. 1574–1609 Add to Reading List Source URL: www2.isye.gatech.edu Language: English - Date: 2011-05-04 08:44:40 Convex optimization Operations research Stochastic approximation Stochastic optimization Convex function Subgradient method Big O notation Ellipsoid method Mathematical optimization Mathematical analysis Convex analysis
63	Online Learning of Nonparametric Mixture Models via Sequential Variational Approximation Dahua Lin Toyota Technological Institute at Chicago Add to Reading List Source URL: papers.nips.cc Language: English - Date: 2014-02-24 18:11:54 Estimation theory Stochastic processes Statistical models Dirichlet process Conjugate prior Mixture model Latent Dirichlet allocation Dirichlet distribution Parametric model Statistics Statistical theory Bayesian statistics
64	A Stochastic PCA Algorithm with an Exponential Convergence Rate Ohad Shamir Weizmann Institute of Science [removed] Add to Reading List Source URL: www.opt-ml.org Language: English - Date: 2014-12-10 11:27:48 Stochastic optimization Singular value decomposition Linear algebra Matrix theory Multivariate statistics Principal component analysis Stochastic approximation Mathematical optimization Stochastic gradient descent Algebra Mathematics Statistics
65	Learning with stochastic proximal gradient Lorenzo Rosasco ∗ DIBRIS, Universit`a di Genova Via Dodecaneso, [removed]Genova, Italy Add to Reading List Source URL: www.opt-ml.org Language: English - Date: 2014-12-10 11:28:36 Stochastic optimization Operations research Stochastic gradient descent Stochastic approximation Gradient descent Gradient method Subgradient method Convex optimization Numerical analysis Mathematical optimization Mathematical analysis
66	Analyzing Feature Generation for Value-Function Approximation Ronald Parr Christopher Painter-Wakefield Department of Computer Science, Duke University, Durham, NC[removed]USA Lihong Li Add to Reading List Source URL: www.cs.duke.edu Language: English - Date: 2007-04-23 20:09:21 Mathematical optimization Dynamic programming Stochastic control Equations Numerical analysis Automatic basis function construction Reinforcement learning Proto-value functions Bellman equation Statistics Mathematics Mathematical analysis
67	Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli Stanford University {jascha,benpoole,sganguli}@stanford.edu Add to Reading List Source URL: www.opt-ml.org Language: English - Date: 2014-12-13 10:45:07 Stochastic optimization Quasi-Newton method Gradient descent Stochastic gradient descent BFGS method Limited-memory BFGS Stochastic approximation Hessian matrix Perceptron Numerical analysis Mathematical optimization Mathematical analysis
68	mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jie Liu Lehigh University Bethlehem, PA 18015 Add to Reading List Source URL: www.opt-ml.org Language: English - Date: 2014-12-10 11:28:41 Stochastic optimization Numerical linear algebra Stochastic gradient descent Gradient method Gradient descent Stochastic approximation Mathematical optimization Random coordinate descent Coordinate descent Numerical analysis Mathematical analysis Mathematics
69	Journal of Machine Learning Research[removed]1149 Submitted 8/02; Published[removed]Least-Squares Policy Iteration Michail G. Lagoudakis Add to Reading List Source URL: www.cs.duke.edu Language: English - Date: 2003-12-20 17:38:33 Dynamic programming Stochastic control Mathematical optimization Markov processes Numerical analysis Reinforcement learning Markov decision process Approximation Least squares Statistics Mathematical analysis Mathematics
70	S2CD: Semi-Stochastic Coordinate Descent Jakub Koneˇcn´y University of Edinburgh United Kingdom, EH9 3FD [removed] Add to Reading List Source URL: www.opt-ml.org Language: English - Date: 2014-12-10 11:28:33 Stochastic optimization Stochastic gradient descent Stochastic approximation Coordinate descent Gradient descent Mathematical optimization Gradient method Gradient Numerical analysis Mathematical analysis Mathematics

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