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Stochastic approximation
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11	STATIONARY TANGENT: THE DISCRETE AND NON-SMOOTH CASE U. KEICH Abstract. In [5] we deﬁne a stationary tangent process, or a locally optimal stationary approximation, to a real non-stationary smooth Gaussian process. Thi Add to Reading List Source URL: www.maths.usyd.edu.au Language: English - Date: 2002-12-09 16:28:18 Mathematical analysis Probability Stochastic processes Stochastic differential equations Markov models Signal processing Stationary process Derivative Spectrum Normal distribution OrnsteinUhlenbeck process Markov chain
12	I will discuss recent work on randomized algorithms for low-rank approximation and principal component analysis (PCA). The talk will focus on efforts that move beyond the extremely fast, but relatively crude approximatio Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-06-23 15:50:48 Algebra Mathematics Multivariate statistics Numerical analysis Numerical linear algebra Iterative methods Dimension reduction Principal component analysis Singular value decomposition Stochastic optimization Nonlinear dimensionality reduction Sparse dictionary learning
13	Simple, Efficient, and Neural Algorithms for Sparse Coding Sanjeev Arora∗ Princeton University, Computer Science Department Add to Reading List Source URL: jmlr.org Language: English - Date: 2015-07-20 20:08:35 Mathematics Numerical analysis Algebra Linear algebra Convex optimization Operations research Computational statistics Mathematical optimization K-SVD Sparse approximation Deep learning Stochastic gradient descent
14	Estimation, Optimization, and Parallelism when Data is Sparse H. Brendan McMahan2 Google, Inc.2 Seattle, WA 98103 Add to Reading List Source URL: stanford.edu Language: English - Date: 2014-09-05 13:17:03 Operations research Numerical analysis Mathematical analysis Numerical linear algebra Applied mathematics Mathematical optimization Online machine learning Sparse approximation Stochastic programming Support vector machine
15	Fluid Approximation for Stochastic Model Checking Jane Hillston joint work with Luca Bortolussi Add to Reading List Source URL: homepages.inf.ed.ac.uk Language: English - Date: 2012-11-02 11:12:32 Probability theory Stochastic processes Statistics Probability Markov models Markov processes Statistical models Stochastic simulation Markov chain Fluid queue Economic model Stochastic
16	SOME EXAMPLES HOW TO USE MEASURE CLASSIFICATION IN NUMBER THEORY ELON LINDENSTRAUSS 1. Introduction 1.1. Ergodic theory has proven itself to be a powerful method to tackle Add to Reading List Source URL: www.ma.huji.ac.il Language: English - Date: 2006-06-15 19:00:10 Ergodic theory Mathematical analysis Mathematics Dynamical systems Stochastic processes Topological groups Diophantine approximation Ergodicity Equidistributed sequence Invariant measure Irrational rotation Mixing
17	Proceedings of Symposia in Applied Mathematics Stochastic Evolutionary Game Dynamics: Foundations, Deterministic Approximation, and Equilibrium Selection William H. Sandholm Add to Reading List Source URL: www.ssc.wisc.edu Language: English - Date: 2011-05-30 11:37:48 Game theory Mathematics Science and technology Evolutionary game theory Probability theory Nash equilibrium Strategy Mathematical optimization Markov chain Best response Normal-form game
18	A sufficient condition for the continuity of permanental processes with applications to local times of Markov processes Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-03-17 20:22:12 Mathematical analysis Analysis Mathematics Fourier analysis Stochastic processes Approximation theory Constructivism Modulus of continuity It diffusion Differential forms on a Riemann surface
19	Online Learning of Nonparametric Mixture Models via Sequential Variational Approximation Dahua Lin Toyota Technological Institute at Chicago Add to Reading List Source URL: dahua.me Language: English - Date: 2013-10-22 19:40:40 Statistics Statistical theory Probability Bayesian statistics Stochastic processes Probability distributions Estimation theory Statistical natural language processing Dirichlet process Mixture model Variational Bayesian methods Dirichlet distribution
20	I will discuss recent work on randomized algorithms for low-rank approximation and principal component analysis (PCA). The talk will focus on efforts that move beyond the extremely fast, but relatively crude approximatio Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-06-23 15:50:48 Algebra Mathematics Multivariate statistics Numerical analysis Dimension reduction Iterative methods Numerical linear algebra Principal component analysis Singular value decomposition Stochastic optimization Algorithm Sparse dictionary learning