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Stochastic optimization
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#	Item
491	Modern Optimization Techniques for Big Data Machine Learning Tong Zhang Rutgers University & Baidu Inc. T. Zhang Add to Reading List Source URL: cikm2014.fudan.edu.cn Language: English - Date: 2014-11-16 09:18:30 Numerical analysis Mathematical analysis Mathematical optimization Operations research Stochastic optimization
492	Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent Rainer Gemulla1 Peter J. Haas2 Add to Reading List Source URL: dws.informatik.uni-mannheim.de Language: English - Date: 2014-09-29 11:40:16 Matrix theory Multivariate statistics Non-negative matrix factorization Matrix Stochastic gradient descent Least squares Mathematical optimization Cholesky decomposition Algebra Mathematics Linear algebra
493	Do you need sophisticated tools for data-based decision analysis? Lawrence Livermore can turn highly complex, multi-modal data sets into information that can be applied to actionable decisions, optimally deployed resourc Add to Reading List Source URL: engineering.llnl.gov Language: English - Date: 2014-10-17 20:45:30 University of California United States Department of Energy National Laboratories Ethology Battelle Memorial Institute Lawrence Livermore National Laboratory Livermore Valley Mathematical optimization Data mining Stochastic optimization Science Formal sciences Knowledge
494	Learning Policy Improvements with Path Integrals Evangelos Theodorou Jonas Buchli Stefan Schaal [removed] Add to Reading List Source URL: www-clmc.usc.edu Language: English - Date: 2011-02-17 11:19:29 Mathematical optimization Dynamic programming Stochastic control Optimal control Markov processes Symbol Markov decision process Continuous function Hamilton–Jacobi–Bellman equation Control theory Statistics Systems theory
495	An Iterative Path Integral Stochastic Optimal Control Approach for Learning Robotic Tasks Evangelos Theodorou ∗ Freek Stulp ∗ Jonas Buchli ∗∗ Stefan Schaal ∗,∗∗∗ ∗ Add to Reading List Source URL: www-clmc.usc.edu Language: English - Date: 2011-04-13 00:25:59 Operations research Mathematical optimization Optimal control Attractor Partial differential equation Path integral formulation Dynamical system Hamilton–Jacobi–Bellman equation Nonlinear system Physics Calculus Control theory
496	The Nature of Mathematical Modeling Neil Gershenfeld PUBLISHED BY THE PRESS SYNDICATE OF THE UNIVERSITY OF CAMBRIDGE The Pitt Building, Trumpington Street, Cambridge CB2 1RP, United Kingdom Add to Reading List Source URL: fab.cba.mit.edu Language: English - Date: 2014-02-03 21:39:33 Differential equations Partial differential equations Mathematical optimization Ordinary differential equation Nonlinear system Mathematical model Finite element method Least squares Stochastic differential equation Calculus Mathematics Mathematical analysis
497	Lifted Parameter Learning in Relational Models Babak Ahmadi1 [removed] Kristian Kersting1,2,3 [removed] Add to Reading List Source URL: www.first-mm.eu Language: English - Date: 2012-07-18 13:16:28 Theoretical computer science M-estimators Stochastic optimization Estimation theory Stochastic gradient descent Markov logic network Conditional random field Gradient boosting Maximum likelihood Statistics Machine learning Probability and statistics
498	STOMP: Stochastic Trajectory Optimization for Motion Planning Add to Reading List Source URL: www-clmc.usc.edu Language: English - Date: 2011-02-17 16:39:08 Expectation–maximization algorithm Missing data Dimensional analysis Econometrics Parametric model Statistics Estimation theory Statistical theory
499	Journal of Machine Learning Research[removed]3197 Submitted 1/10; Revised 7/10; Published[removed]A Generalized Path Integral Control Approach to Reinforcement Learning Add to Reading List Source URL: www-clmc.usc.edu Language: English - Date: 2011-05-25 14:46:58 Mathematical optimization Optimal control Dynamic programming Equations Stochastic control Hamilton–Jacobi–Bellman equation Markov chain Stochastic differential equation Path integral formulation Control theory Statistics Systems theory
500	Variable Impedance Control A Reinforcement Learning Approach Jonas Buchli, Evangelos Theodorou, Freek Stulp, Stefan Schaal Abstract— One of the hallmarks of the performance, versatility, and robustness of biological mo Add to Reading List Source URL: www-clmc.usc.edu Language: English - Date: 2011-02-17 00:49:52 Mathematical optimization Dynamic programming Stochastic control Optimal control Operations research Reinforcement learning Robotics Humanoid robot Markov decision process Control theory Statistics Science

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