Gradient descent

Results: 277



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241MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

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Source URL: cbcl.mit.edu

Language: English - Date: 2001-04-10 14:19:22
242Optimization A framework for predictive analytics Matt Gattis, Hunch.com Simple Optimization Problem

Optimization A framework for predictive analytics Matt Gattis, Hunch.com Simple Optimization Problem

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Source URL: files.meetup.com

Language: English - Date: 2010-11-13 08:28:33
243g2o: A General Framework for Graph Optimization Rainer K¨ummerle Giorgio Grisetti  Hauke Strasdat

g2o: A General Framework for Graph Optimization Rainer K¨ummerle Giorgio Grisetti Hauke Strasdat

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Source URL: ais.informatik.uni-freiburg.de

Language: English - Date: 2011-02-09 03:49:00
244MEAN-NORMALIZED STOCHASTIC GRADIENT FOR LARGE-SCALE DEEP LEARNING Simon Wiesler1 , Alexander Richard1 , Ralf Schl¨uter1 , Hermann Ney1,2 1 Human Language Technology and Pattern Recognition, Computer Science Department,

MEAN-NORMALIZED STOCHASTIC GRADIENT FOR LARGE-SCALE DEEP LEARNING Simon Wiesler1 , Alexander Richard1 , Ralf Schl¨uter1 , Hermann Ney1,2 1 Human Language Technology and Pattern Recognition, Computer Science Department,

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Source URL: www-i6.informatik.rwth-aachen.de

Language: English
245MEAN-NORMALIZED STOCHASTIC GRADIENT FOR LARGE-SCALE DEEP LEARNING Simon Wiesler1 , Alexander Richard1 , Ralf Schl¨uter1 , Hermann Ney1,2 1 Human Language Technology and Pattern Recognition, Computer Science Department,

MEAN-NORMALIZED STOCHASTIC GRADIENT FOR LARGE-SCALE DEEP LEARNING Simon Wiesler1 , Alexander Richard1 , Ralf Schl¨uter1 , Hermann Ney1,2 1 Human Language Technology and Pattern Recognition, Computer Science Department,

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Source URL: www-i6.informatik.rwth-aachen.de

Language: English
246Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu, Benjamin Recht, Christopher R´e and Stephen J. Wright Computer Sciences Department, University of Wisconsin-Madison 1210 W Dayton St,

Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu, Benjamin Recht, Christopher R´e and Stephen J. Wright Computer Sciences Department, University of Wisconsin-Madison 1210 W Dayton St,

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Source URL: www.eecs.berkeley.edu

Language: English - Date: 2013-08-22 23:36:09
24714  IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 18, NO. 1, JANUARY 2007 Backpropagation Algorithms for a Broad Class of Dynamic Networks

14 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 18, NO. 1, JANUARY 2007 Backpropagation Algorithms for a Broad Class of Dynamic Networks

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Source URL: hagan.ecen.ceat.okstate.edu

Language: English - Date: 2009-12-17 20:17:10
24814  IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 18, NO. 1, JANUARY 2007 Backpropagation Algorithms for a Broad Class of Dynamic Networks

14 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 18, NO. 1, JANUARY 2007 Backpropagation Algorithms for a Broad Class of Dynamic Networks

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Source URL: hagan.okstate.edu

Language: English - Date: 2009-12-17 20:17:10
249Parallelized Stochastic Gradient Descent Markus Weimer Yahoo! Labs Sunnyvale, CA[removed]removed]

Parallelized Stochastic Gradient Descent Markus Weimer Yahoo! Labs Sunnyvale, CA[removed]removed]

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Source URL: martin.zinkevich.org

Language: English - Date: 2010-10-30 00:56:22
250Parallel Boosting with Momentum Indraneel Mukherjee, Kevin Canini, Rafael Frongillo? , and Yoram Singer Google Inc. Abstract. We describe a new, simplified, and general analysis of a fusion of Nesterov’s accelerated gr

Parallel Boosting with Momentum Indraneel Mukherjee, Kevin Canini, Rafael Frongillo? , and Yoram Singer Google Inc. Abstract. We describe a new, simplified, and general analysis of a fusion of Nesterov’s accelerated gr

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Source URL: canini.me

Language: English - Date: 2013-06-29 02:08:53