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Gradient descent
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#	Item
171	Yurii Nesterov http://www.core.ucl.ac.be/~nesterov Nesterov’s Optimal Gradient Methods Xinhua Zhang Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2009-10-30 11:36:41 Gradient descent Numerical analysis Mathematical optimization Operations research
172	AN ANALYSIS OF THE EXPONENTIATED GRADIENT DESCENT ALGORITHM Simon I. Hill Robert C. Williamson Telecommunications Engineering, RSISE Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 05:32:38 Mean squared error Least mean squares filter Algorithm Statistics Least squares Estimation theory
173	Online Learning via Congregational Gradient Descent Kim L. Blackmore Robert C. Williamson William A. Sethares Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 04:23:22 Regression analysis Operations research Genetic algorithm Nonlinear regression Gradient descent Levenberg–Marquardt algorithm Expectation–maximization algorithm Numerical analysis Mathematical optimization Applied mathematics
174	IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 50, NO. 8, AUGUST[removed]Exploiting Sparsity in Adaptive Filters Richard K. Martin, William A. Sethares, Robert C. Williamson, and C. Richard Johnson, Jr., Fellow, IEEE Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-16 18:13:14 Filter theory Least mean squares filter Sparse matrix Gradient descent Numerical analysis Digital signal processing Mathematics
175	Journal of Machine Learning Research[removed]746 Submitted 11/07; Revised 7/08; Published 3/09 Nieme: Large-Scale Energy-Based Models Francis Maes Add to Reading List Source URL: www.jmlr.org Language: English - Date: 2009-03-26 17:45:20 Econometrics Perceptron Backpropagation Support vector machine Supervised learning Stochastic gradient descent Loss function Regression analysis Multilayer perceptron Statistics Machine learning Neural networks
176	Online Learning with Kernels Jyrki Kivinen Alex J. Smola Robert C. Williamson Research School of Information Sciences and Engineering Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 08:39:23 Statistical theory Computational statistics Neural networks Computational neuroscience Support vector machine Stochastic gradient descent Perceptron Loss function Robust statistics Statistics Machine learning Econometrics
177	Local Minima and Attractors at In nity for Gradient Descent Learning Algorithms Kim L. Blackmore Robert C. Williamson Iven M.Y. Mareels June 21, 1995 Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 04:18:54 Expected value Mathematics Environmental science Parameter Parametrization
178	Smoothing DCG for Learning to Rank: A Novel Approach Using Smoothed Hinge Functions Mingrui Wu, Yi Chang, Zhaohui Zheng Web Search Ranking Group, Yahoo! Labs, 701 First Avenue, Sunnyvale, CA 94089 Add to Reading List Source URL: www.yichang-cs.com Language: English - Date: 2009-11-16 16:19:12 Learning to rank Artificial intelligence Science Discounted cumulative gain Mathematical optimization Gradient boosting Gradient descent Ranking function Information science Machine learning Information retrieval
179	Notes 3 Statistical Machine Learning Empirical Risk Minimization and Optimization Instructor: Justin Domke Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2011-11-07 14:35:34 Convex analysis Differential calculus Operations research Multivariable calculus Convex optimization Gradient descent Empirical risk minimization Convex function Gradient Mathematical analysis Mathematical optimization Mathematics
180	6.867 Machine learning, lecture 13 (Jaakkola) 1 Lecture topics: • Boosting, margin, and gradient descent Add to Reading List Source URL: ocw.mit.edu Language: English - Date: 2015-03-15 16:36:56 AdaBoost Boosting Perceptron Computer programming Ensemble learning Learning Statistics

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