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Gradient descent
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#	Item
51	Rectified Factor Networks Supplement Djork-Arn´e Clevert, Andreas Mayr, Thomas Unterthiner and Sepp Hochreiter Institute of Bioinformatics, Johannes Kepler University, Linz, Austria {okko,mayr,unterthiner,hochreit}@bioi Add to Reading List Source URL: www.bioinf.jku.at Language: English - Date: 2015-12-02 09:40:10 Linear algebra Functional analysis Projection Mathematical optimization Expectationmaximization algorithm Gradient descent Matrix
52	MO Mathematical Optimization Copyright (C) 1991, 1992, 1993, 1994, 1995 by the Computational Science Education Project This electronic book is copyrighted, and protected by the copyright laws of the United States. Add to Reading List Source URL: www.aiinfinance.com Language: English - Date: 2012-06-26 15:07:16 Mathematical optimization Hessian matrix Gradient descent Constrained optimization Global optimization Optimization problem Convex function Function of several real variables Convex optimization Quadratic programming
53	Managed Communication and Consistency for Fast Data-Parallel Iterative Analytics Jinliang Wei Wei Dai Aurick Qiao Qirong Ho? Henggang Cui Gregory R. Ganger Phillip B. Gibbons† Garth A. Gibson Eric P. Xing Carnegie Mell Add to Reading List Source URL: www.pdl.cmu.edu Language: English - Date: 2016-03-07 13:00:52 Parallel computing Stochastic optimization M-estimators Convex optimization Stochastic gradient descent Consistency model Cache Parameter ML XC Bulk synchronous parallel
54	277 Documenta Math. Subgradient Optimization in Nonsmooth Optimization Add to Reading List Source URL: documenta.sagemath.org Language: English - Date: 2012-07-25 10:25:10 Mathematical optimization Subgradient method Subderivative Gradient descent Relaxation Cutting-plane method Convex optimization
55	Revisiting natural gradient for deep networks Yoshua Bengio Universit´e de Montr´eal Montr´eal QC H3C 3J7 Canada Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-02-18 01:51:44 Estimation theory Numerical linear algebra M-estimators Stochastic optimization Least squares Conjugate gradient method Nonlinear conjugate gradient method Gradient descent Gradient method Hessian matrix Fisher information BroydenFletcherGoldfarbShanno algorithm
56	FireCaffe: near-linear acceleration of deep neural network training on compute clusters Forrest N. Iandola, Khalid Ashraf, Matthew W. Moskewicz, Kurt Keutzer DeepScale∗ and UC Berkeley arXiv:1511.00175v2 [cs.CV] 8 Jan Add to Reading List Source URL: arxiv.org Language: English - Date: 2016-01-10 20:23:29 Graphics hardware GPGPU Parallel computing Computational neuroscience Artificial neural networks Convolutional neural network Graphics processing unit Speech recognition GPU cluster CUDA Kepler Stochastic gradient descent
57	Published as a conference paper at ICLRA DAM : A M ETHOD FOR S TOCHASTIC O PTIMIZATION Diederik P. Kingma* University of Amsterdam Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-07-26 20:01:45 M-estimators Computational statistics Computational neuroscience Estimation theory Stochastic optimization Stochastic gradient descent Deep learning Artificial neural network Convolutional neural network Mathematical optimization Loss function Feature learning
58	arXiv:1410.7455v8 [cs.NE] 22 Jun 2015 Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-06-23 20:50:51 Stochastic optimization Estimation theory Computational statistics M-estimators Convex optimization Stochastic gradient descent Matrix Fisher information Deep learning Covariance matrix
59	Efficient Learning of Mahalanobis Metrics for Ranking Daryl K. H. Lim DKLIM @ UCSD . EDU Department of Electrical and Computer Engineering, University of California, San Diego, CAUSA Gert Lanckriet Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:24 Machine learning Learning to rank Support vector machine XQ Valuation Supervised learning Stochastic gradient descent
60	Energetic Natural Gradient Descent Philip S. Thomas Bruno Castro da Silva Christoph Dann Emma Brunskill Add to Reading List Source URL: psthomas.com Language: English - Date: 2016-05-27 10:07:35 Statistical theory Estimation theory Parametric model Loss function Fisher information Expectationmaximization algorithm Divergence

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