| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Deep Learning in Natural Language Processing by Ronan Collobert, Jason Weston, 2010 (rec 2009)/1.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Deep Learning in Natural Language Processing by Ronan Collobert, Jason Weston, 2010 (rec 2009)/2.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Deep Learning in Natural Language Processing by Ronan Collobert, Jason Weston, 2010 (rec 2009)/slide_descr.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Deep Learning in Natural Language Processing by Ronan Collobert, Jason Weston, 2010 (rec 2009)/slides.pdf |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Deep Learning in Natural Language Processing by Ronan Collobert, Jason Weston, 2010 (rec 2009)/url.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Deep Learning with Multiplicative Interactions by Geoffrey E. Hinton, 2010 (rec 2009)/1.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Learning and Inference in Low-Level Vision by Yair Weiss, 2010 (rec 2009)/1.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Learning and Inference in Low-Level Vision by Yair Weiss, 2010 (rec 2009)/slide_descr.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Learning and Inference in Low-Level Vision by Yair Weiss, 2010 (rec 2009)/slides.pdf |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Learning and Inference in Low-Level Vision by Yair Weiss, 2010 (rec 2009)/url.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Making Very Large-Scale Linear Algebraic Computations Possible Via Randomization by Gunnar Martinsson, 2010 (rec 2009)/1.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Making Very Large-Scale Linear Algebraic Computations Possible Via Randomization by Gunnar Martinsson, 2010 (rec 2009)/2.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Making Very Large-Scale Linear Algebraic Computations Possible Via Randomization by Gunnar Martinsson, 2010 (rec 2009)/url.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Model-Based Reinforcement Learning by Michael Littman, 2010 (rec 2009)/1.flv |
169.4 MB |
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145.3 MB |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Relative Entropy by Sergio Verdu, 2010 (rec 2009)/1.flv |
179 MB |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Sequential Monte-Carlo Methods by Arnaud Doucet, Nando de Freitas, 2010 (rec 2009)/1.flv |
343.7 MB |
| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Sequential Monte-Carlo Methods by Arnaud Doucet, Nando de Freitas, 2010 (rec 2009)/2.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Sparse Methods for Machine Learning: Theory and Algorithms by Francis R. Bach, 2010 (rec 2009)/1.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Sparse Methods for Machine Learning: Theory and Algorithms by Francis R. Bach, 2010 (rec 2009)/2.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/Sparse Methods for Machine Learning: Theory and Algorithms by Francis R. Bach, 2010 (rec 2009)/slide_descr.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/The Rat Vibrissal Array as a Model Sensorimotor System by Mitra Hartmann, 2010 (rec 2009)/1.flv |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/The Rat Vibrissal Array as a Model Sensorimotor System by Mitra Hartmann, 2010 (rec 2009)/slide_descr.txt |
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| videolectures.net/23rd Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2009/The Rat Vibrissal Array as a Model Sensorimotor System by Mitra Hartmann, 2010 (rec 2009)/url.txt |
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| videolectures.net/24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010/Optimization Algorithms in Machine Learning by Stephen J. Wright, 2011 (rec 2010)/1.flv |
226.3 MB |
| videolectures.net/24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010/Optimization Algorithms in Machine Learning by Stephen J. Wright, 2011 (rec 2010)/2.flv |
232.4 MB |
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| videolectures.net/24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010/Reinforcement Learning in Humans and Other Animals by Nathaniel Daw, 2011 (rec 2010)/1.flv |
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| videolectures.net/24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010/Reinforcement Learning in Humans and Other Animals by Nathaniel Daw, 2011 (rec 2010)/2.flv |
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| videolectures.net/24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010/Reinforcement Learning in Humans and Other Animals by Nathaniel Daw, 2011 (rec 2010)/slides.pdf |
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| videolectures.net/24th Annual International Conference on Machine Learning (ICML), Corvallis 2007/Best Paper - Information-Theoretic Metric Learning by Brian Kulis, 2007/1.flv |
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| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/A Factor Model for Learning Higher Order Features in Natural Images by Yan Karklin, 2009/1.flv |
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| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/Matrix Computations in Machine Learning by Inderjit S. Dhillon, 2009/1.flv |
183.5 MB |
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| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/Tutorial on Learning Deep Architectures by Yoshua Bengio, Yann LeCun, 2009/1.flv |
96 MB |
| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/Tutorial on Learning Deep Architectures by Yoshua Bengio, Yann LeCun, 2009/2.flv |
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| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/Tutorial on Learning Deep Architectures by Yoshua Bengio, Yann LeCun, 2009/slides2.pdf |
11 MB |
| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/Tutorial on Learning Deep Architectures by Yoshua Bengio, Yann LeCun, 2009/url.txt |
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| videolectures.net/26th International Conference on Machine Learning (ICML), Montreal 2009/Unsupervised Discovery of Structure, Succinct Representations and Sparsity by Andrew Y. Ng, 2009/1.flv |
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| videolectures.net/Autumn School 2006: Machine Learning over Text and Images - Pittsburgh/Semisupervised Learning Approaches by Tom Mitchell, 2007 (rec 2006)/1.flv |
180.8 MB |
| videolectures.net/Autumn School 2006: Machine Learning over Text and Images - Pittsburgh/Semisupervised Learning Approaches by Tom Mitchell, 2007 (rec 2006)/slide_descr.txt |
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| videolectures.net/CERN Summer School 2009/Introduction to Statistics by Glen Cowan, 2010 (rec 2009)/1.flv |
244.2 MB |
| videolectures.net/CERN Summer School 2009/Introduction to Statistics by Glen Cowan, 2010 (rec 2009)/2.flv |
245.8 MB |
| videolectures.net/CERN Summer School 2009/Introduction to Statistics by Glen Cowan, 2010 (rec 2009)/3.flv |
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| videolectures.net/CERN Summer School 2009/Introduction to Statistics by Glen Cowan, 2010 (rec 2009)/4.flv |
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| videolectures.net/CERN Summer School 2009/Introduction to Statistics by Glen Cowan, 2010 (rec 2009)/slides2a.pdf |
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| videolectures.net/CERN Summer School 2009/Introduction to Statistics by Glen Cowan, 2010 (rec 2009)/slides4a.pdf |
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| videolectures.net/CERN Summer School 2010/Introduction to Statistics by Glen Cowan, 2011 (rec 2010)/1.flv |
232.5 MB |
| videolectures.net/CERN Summer School 2010/Introduction to Statistics by Glen Cowan, 2011 (rec 2010)/2.flv |
229.7 MB |
| videolectures.net/CERN Summer School 2010/Introduction to Statistics by Glen Cowan, 2011 (rec 2010)/3.flv |
243.2 MB |
| videolectures.net/CERN Summer School 2010/Introduction to Statistics by Glen Cowan, 2011 (rec 2010)/4.flv |
231.6 MB |
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| videolectures.net/EPSRC Winter School in Mathematics for Data Modelling, Sheffield 2008/Introduction to Support Vector Machines by Colin Campbell, 2008/1.flv |
140.9 MB |
| videolectures.net/EPSRC Winter School in Mathematics for Data Modelling, Sheffield 2008/Introduction to Support Vector Machines by Colin Campbell, 2008/2.flv |
98.2 MB |
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| videolectures.net/Gaussian Processes in Practice Workshop, Bletchley Park 2006/Gaussian Process Basics by David MacKay, 2007 (rec 2006)/1.flv |
184.9 MB |
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| videolectures.net/MIT World Host: Computer Science and Artificial Intelligence Laboratory (CSAIL)/Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind by Marvin Minsky, 2011 (rec 2007)/1.flv |
264.6 MB |
| videolectures.net/MIT World Host: Computer Science and Artificial Intelligence Laboratory (CSAIL)/Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind by Marvin Minsky, 2011 (rec 2007)/descr.txt |
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| videolectures.net/MIT World Host: Computer Science and Artificial Intelligence Laboratory (CSAIL)/Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind by Marvin Minsky, 2011 (rec 2007)/slide_descr.txt |
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| videolectures.net/MIT World Host: Computer Science and Artificial Intelligence Laboratory (CSAIL)/Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind by Marvin Minsky, 2011 (rec 2007)/url.txt |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Advanced Statistical Learning Theory by Olivier Bousquet, 2007 (rec 2004)/1.flv |
274.9 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Advanced Statistical Learning Theory by Olivier Bousquet, 2007 (rec 2004)/2.flv |
191.9 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Advanced Statistical Learning Theory by Olivier Bousquet, 2007 (rec 2004)/3.flv |
340.1 MB |
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384 KB |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Advanced Statistical Learning Theory by Olivier Bousquet, 2007 (rec 2004)/slides_small3.pdf |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/1.flv |
129.2 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/2.flv |
127 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/3.flv |
127.8 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/4.flv |
135.2 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/5.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/slides_small3.pdf |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/slides_small4.pdf |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Markov Chain Monte Carlo Methods by Christian Robert, 2007 (rec 2004)/slides_small5.pdf |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/1.flv |
133.2 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/2.flv |
107.2 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/3.flv |
129.2 MB |
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108 MB |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/6.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/7.flv |
161.7 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/8.flv |
127.6 MB |
| videolectures.net/Machine Learning Summer School (MLSS), Berder Island 2004/Statistical Learning Theory by John Shawe-Taylor, 2007 (rec 2004)/answers.pdf |
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| videolectures.net/Machine Learning Summer School (MLSS), Bordeaux 2011/Convex Optimization by Lieven Vandenberghe, 2011/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Bordeaux 2011/Graphical Models and message-passing algorithms by Martin J. Wainwright, 2011/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Bordeaux 2011/Kernel Methods by Bernhard Schölkopf, 2011/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Bordeaux 2011/Learning Theory: statistical and game-theoretic approaches by Nicolò Cesa-Bianchi, 2011/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Bordeaux 2011/Monte Carlo Methods by Arnaud Doucet, 2011/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Approximate Inference by Tom Minka, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Bayesian or Frequentist, Which Are You? by Michael I. Jordan, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Computer Vision by Andrew Blake, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Deep Belief Networks by Geoffrey E. Hinton, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Gaussian Processes by Carl Edward Rasmussen, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Information Theory by David MacKay, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Introduction To Bayesian Inference by Christopher Bishop, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Learning Theory by John Shawe-Taylor, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Markov Chain Monte Carlo by Iain Murray, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Cambridge 2009/Reinforcement Learning by Michael Littman, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Canberra 2005/Gradient Methods for Machine Learning by Nicol Schraudolph, 2007 (rec 2005)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Canberra 2010/Online Learning by Peter L. Bartlett, 2011 (rec 2010)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2005/Energy-based models & Learning for Invariant Image Recognition by Yann LeCun, 2007 (rec 2005)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2005/Trees for Regression and Classification by Robert Nowak, 2007 (rec 2005)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Bounding Excess Risk in Machine Learning by Vladimir Koltchinskii, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Fitting a Graph to Vector Data by Daniel A. Spielman, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/How to Visualize the Unseeable by Xiaochuan Pan, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Kernel Methods and Support Vector Machines by John Shawe-Taylor, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Learning Dictionaries for Image Analysis and Sensing by Guillermo Sapiro, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Learning Feature Hierarchies by Yann LeCun, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Matrix Completion via Convex Optimization: Theory and Algorithms by Emmanuel Candes, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Optimization Algorithms in Support Vector Machines by Stephen J. Wright, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Semi-Supervised Learning by Jerry (Xiaojin) Zhu, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Sparse Representations from Inverse Problems to Pattern Recognition by Stéphane Mallat, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Theory and Applications of Boosting by Robert Schapire, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Chicago 2009/Unsupervised Learning for Stereo Vision by David McAllester, 2009/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Kioloa 2008/Foundations of Machine Learning by Marcus Hutter, 2008/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Kioloa 2008/Introduction to Reinforcement Learning by Csaba Szepesvari, 2008/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Kioloa 2008/Learning in Computer Vision by Simon Lucey, 2008/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Kioloa 2008/Monte Carlo Simulation for Statistical Inference, Model Selection and Decision Making by Nando de Freitas, 2008/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Taipei 2006/Introduction to Boosting by Gunnar Rätsch, 2007 (rec 2006)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Taipei 2006/Machine Learning, Probability and Graphical Models by Sam Roweis, 2007 (rec 2006)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Tübingen 2003/Empirical Inference by Vladimir Vapnik, 2007 (rec 2003)/1.flv |
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| videolectures.net/Machine Learning Summer School (MLSS), Tübingen 2003/Some Mathematical Tools for Machine Learning by Chris Burges, 2007 (rec 2003)/1.flv |
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| videolectures.net/Machine Learning seminars at the Cambridge University Engineering Department/Group Theory and Machine Learning by Risi Kondor, 2008 (rec 2007)/1.flv |
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| videolectures.net/NATO Advanced Study Institute on Mining Massive Data Sets for Security/Foundations of Statistical Learning Theory - Empirical Inference in high-dimention spaces by Léon Bottou, Vladimir Vapnik, 2007/1.flv |
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| videolectures.net/NATO Advanced Study Institute on Mining Massive Data Sets for Security/Foundations of Statistical Learning Theory - Empirical Inference in high-dimention spaces by Léon Bottou, Vladimir Vapnik, 2007/slide_descr.txt |
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| videolectures.net/NIPS Workshop on Dynamical Systems, Stochastic Processes and Bayesian Inference, Whistler 2006/A Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov Processes by Chris Williams, 2007 (rec 2006)/1.flv |
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| videolectures.net/NIPS Workshop on Dynamical Systems, Stochastic Processes and Bayesian Inference, Whistler 2006/A Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov Processes by Chris Williams, 2007 (rec 2006)/slide_descr.txt |
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| videolectures.net/NIPS Workshop on Dynamical Systems, Stochastic Processes and Bayesian Inference, Whistler 2006/A Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov Processes by Chris Williams, 2007 (rec 2006)/url.txt |
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| videolectures.net/NIPS Workshop on Efficient Machine Learning, Whistler 2007/Interview with Yann LeCun by Yann LeCun, 2008 (rec 2007)/1.flv |
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| videolectures.net/NIPS Workshop on Efficient Machine Learning, Whistler 2007/Who is Afraid of Non-Convex Loss Functions? by Yann LeCun, 2007/1.flv |
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| videolectures.net/NIPS Workshop on Efficient Machine Learning, Whistler 2007/Who is Afraid of Non-Convex Loss Functions? by Yann LeCun, 2007/url.txt |
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| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Learning Similarity Metrics with Invariance Properties by Yann LeCun, 2007 (rec 2006)/1.flv |
160.9 MB |
| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Learning Similarity Metrics with Invariance Properties by Yann LeCun, 2007 (rec 2006)/slide_descr.txt |
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| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Learning Similarity Metrics with Invariance Properties by Yann LeCun, 2007 (rec 2006)/slides.pdf |
13.1 MB |
| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Learning Similarity Metrics with Invariance Properties by Yann LeCun, 2007 (rec 2006)/url.txt |
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| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Neighbourhood Components Analysis and Metric Learning by Sam Roweis, 2007 (rec 2006)/1.flv |
141 MB |
| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Neighbourhood Components Analysis and Metric Learning by Sam Roweis, 2007 (rec 2006)/slide_descr.txt |
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| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Neighbourhood Components Analysis and Metric Learning by Sam Roweis, 2007 (rec 2006)/slides.pdf |
521 KB |
| videolectures.net/NIPS Workshop on Learning to Compare Examples, Whistler 2006/Neighbourhood Components Analysis and Metric Learning by Sam Roweis, 2007 (rec 2006)/url.txt |
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| videolectures.net/NIPS Workshop on Optimization for Machine Learning, Whistler 2008/Large-scale Machine Learning and Stochastic Algorithms by Léon Bottou, 2008/1.flv |
152.4 MB |
| videolectures.net/NIPS Workshop on Optimization for Machine Learning, Whistler 2008/Large-scale Machine Learning and Stochastic Algorithms by Léon Bottou, 2008/url.txt |
42 B |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Cosmology meets Machine Learning/Efficient Estimation of N-point Spatial Statistics by Alexander G. Gray, 2012 (rec 2011)/1.flv |
21.4 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Cosmology meets Machine Learning/Efficient Estimation of N-point Spatial Statistics by Alexander G. Gray, 2012 (rec 2011)/slide_descr.txt |
177 B |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Cosmology meets Machine Learning/Efficient Estimation of N-point Spatial Statistics by Alexander G. Gray, 2012 (rec 2011)/slides.pdf |
1.2 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Cosmology meets Machine Learning/Efficient Estimation of N-point Spatial Statistics by Alexander G. Gray, 2012 (rec 2011)/url.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Efficiency of Quasi-Newton Methods on Strictly Positive Functions by Yurii Nesterov, 2011 (rec 2010)/1.flv |
202.7 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Efficiency of Quasi-Newton Methods on Strictly Positive Functions by Yurii Nesterov, 2011 (rec 2010)/slide_descr.txt |
5 KB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Efficiency of Quasi-Newton Methods on Strictly Positive Functions by Yurii Nesterov, 2011 (rec 2010)/slides.pdf |
1.2 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Efficiency of Quasi-Newton Methods on Strictly Positive Functions by Yurii Nesterov, 2011 (rec 2010)/url.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Fast first-order methods for convex optimization with line search by Katya Scheinberg, 2012 (rec 2011)/1.flv |
97.3 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Fast first-order methods for convex optimization with line search by Katya Scheinberg, 2012 (rec 2011)/slide_descr.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Fast first-order methods for convex optimization with line search by Katya Scheinberg, 2012 (rec 2011)/slides.pdf |
2.3 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Fast first-order methods for convex optimization with line search by Katya Scheinberg, 2012 (rec 2011)/url.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Limited-memory quasi-Newton and Hessianfree Newton methods for non-smooth optimization by Mark Schmidt, 2011 (rec 2010)/1.flv |
212.9 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Limited-memory quasi-Newton and Hessianfree Newton methods for non-smooth optimization by Mark Schmidt, 2011 (rec 2010)/slide_descr.txt |
9 KB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Limited-memory quasi-Newton and Hessianfree Newton methods for non-smooth optimization by Mark Schmidt, 2011 (rec 2010)/slides.pdf |
1.1 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Limited-memory quasi-Newton and Hessianfree Newton methods for non-smooth optimization by Mark Schmidt, 2011 (rec 2010)/url.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Lock-Free Approaches to Parallelizing Stochastic Gradient Descent by Benjamin Recht, 2012 (rec 2011)/1.flv |
243.7 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Lock-Free Approaches to Parallelizing Stochastic Gradient Descent by Benjamin Recht, 2012 (rec 2011)/slide_descr.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Lock-Free Approaches to Parallelizing Stochastic Gradient Descent by Benjamin Recht, 2012 (rec 2011)/slides.pdf |
2.3 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Lock-Free Approaches to Parallelizing Stochastic Gradient Descent by Benjamin Recht, 2012 (rec 2011)/url.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization by Ohad Samir, 2012 (rec 2011)/1.flv |
92.7 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization by Ohad Samir, 2012 (rec 2011)/slide_descr.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization by Ohad Samir, 2012 (rec 2011)/slides.pdf |
224 KB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Optimization for Machine Learning/Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization by Ohad Samir, 2012 (rec 2011)/url.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Relations between machine learning problems – an approach to unify the field/Relations Betweeen Machine Learning Problems by Robert C. Williamson, 2012 (rec 2011)/1.flv |
114.5 MB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Relations between machine learning problems – an approach to unify the field/Relations Betweeen Machine Learning Problems by Robert C. Williamson, 2012 (rec 2011)/slide_descr.txt |
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| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Relations between machine learning problems – an approach to unify the field/Relations Betweeen Machine Learning Problems by Robert C. Williamson, 2012 (rec 2011)/slides.pdf |
817 KB |
| videolectures.net/NIPS Workshops, Sierra Nevada 2011/Relations between machine learning problems – an approach to unify the field/Relations Betweeen Machine Learning Problems by Robert C. Williamson, 2012 (rec 2011)/url.txt |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Marseille 2010/Introduction to Machine Learning by Iain Murray, 2010/1.flv |
221.8 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Marseille 2010/Introduction to Machine Learning by Iain Murray, 2010/2.flv |
234.4 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Marseille 2010/Introduction to Machine Learning by Iain Murray, 2010/3.flv |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Marseille 2010/Introduction to Machine Learning by Iain Murray, 2010/slide_descr.txt |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Marseille 2010/Introduction to Machine Learning by Iain Murray, 2010/slides_small2.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Marseille 2010/Introduction to Machine Learning by Iain Murray, 2010/slides_small3.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/1.flv |
117.1 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/2.flv |
100.1 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/3.flv |
80.8 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/4.flv |
229.4 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/5.flv |
124.6 MB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slide_descr.txt |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides1a.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides1b.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides2a.pdf |
280 KB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides2b.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides3a.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides3b.pdf |
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| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides4.pdf |
70 KB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides5a.pdf |
232 KB |
| videolectures.net/PASCAL Bootcamp in Machine Learning, Vilanova 2007/Basics of probability and statistics by Mikaela Keller, 2007/slides5b.pdf |
70 KB |
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| videolectures.net/Single Lectures Series/A tutorial on Deep Learning by Geoffrey E. Hinton, 2009/1.flv |
191.9 MB |
| videolectures.net/Single Lectures Series/A tutorial on Deep Learning by Geoffrey E. Hinton, 2009/2.flv |
202.4 MB |
| videolectures.net/Single Lectures Series/A tutorial on Deep Learning by Geoffrey E. Hinton, 2009/descr.txt |
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| videolectures.net/Single Lectures Series/A tutorial on Deep Learning by Geoffrey E. Hinton, 2009/slides.pdf |
3 MB |
| videolectures.net/Single Lectures Series/A tutorial on Deep Learning by Geoffrey E. Hinton, 2009/url.txt |
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| videolectures.net/Single Lectures Series/Learning Deep Hierarchies of Representations by Yoshua Bengio, 2009/1.flv |
40.1 MB |
| videolectures.net/Single Lectures Series/Learning Deep Hierarchies of Representations by Yoshua Bengio, 2009/descr.txt |
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| videolectures.net/Single Lectures Series/Learning Deep Hierarchies of Representations by Yoshua Bengio, 2009/slides.pdf |
3.8 MB |
| videolectures.net/Single Lectures Series/Learning Deep Hierarchies of Representations by Yoshua Bengio, 2009/url.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Computer vision by Richard Hartley, 2009/1.flv |
328.4 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Computer vision by Richard Hartley, 2009/2.flv |
316.5 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Computer vision by Richard Hartley, 2009/3.flv |
352.2 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Computer vision by Richard Hartley, 2009/slide_descr.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Computer vision by Richard Hartley, 2009/slides.pdf |
5 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Computer vision by Richard Hartley, 2009/url.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/1.flv |
250.7 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/2.flv |
434.1 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/3.flv |
324.6 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/4.flv |
293.2 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/5.flv |
311.7 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/6.flv |
192.9 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Graphical models by Tibério Caetano, 2009/slide_descr.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Group Theory in Machine Learning by Marconi Barbosa, 2009/1.flv |
164.7 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Group Theory in Machine Learning by Marconi Barbosa, 2009/2.flv |
161.5 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Group Theory in Machine Learning by Marconi Barbosa, 2009/3.flv |
176.9 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Group Theory in Machine Learning by Marconi Barbosa, 2009/slide_descr.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Group Theory in Machine Learning by Marconi Barbosa, 2009/slides.pdf |
7.7 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Group Theory in Machine Learning by Marconi Barbosa, 2009/url.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Learning Theory by Mark Reid, 2009/1.flv |
195.8 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Learning Theory by Mark Reid, 2009/2.flv |
167.8 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Learning Theory by Mark Reid, 2009/3.flv |
131.3 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Learning Theory by Mark Reid, 2009/slide_descr.txt |
8 KB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Learning Theory by Mark Reid, 2009/slides.pdf |
14.9 MB |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/1.flv |
166.5 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/2.flv |
166.5 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/3.flv |
153 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/4.flv |
151 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/5.flv |
138.9 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/6.flv |
124.4 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/slide_descr.txt |
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| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/slides.pdf |
3.2 MB |
| videolectures.net/Summer Schools in Logic and Learning, Canberra 2009/Reinforcement learning by Scott Sanner, 2009/url.txt |
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| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/From Trees to Forests and Rule Sets - A Unified Overview of Ensemble Methods by John Elder, Giovanni Seni, 2007/1.flv |
168.3 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/From Trees to Forests and Rule Sets - A Unified Overview of Ensemble Methods by John Elder, Giovanni Seni, 2007/2.flv |
298.7 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/From Trees to Forests and Rule Sets - A Unified Overview of Ensemble Methods by John Elder, Giovanni Seni, 2007/slide_descr.txt |
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| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/From Trees to Forests and Rule Sets - A Unified Overview of Ensemble Methods by John Elder, Giovanni Seni, 2007/slides.pdf |
1.9 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/From Trees to Forests and Rule Sets - A Unified Overview of Ensemble Methods by John Elder, Giovanni Seni, 2007/url.txt |
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| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/1.flv |
229.7 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/2.flv |
229.8 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/3.flv |
18 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/slide_descr.txt |
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| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/slides1.ppt |
1.1 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/slides2.ppt |
1.1 MB |
| videolectures.net/The 13th International Conference on Knowledge Discovery and Data Mining/Learning Bayesian Networks by Richard E. Neapolitan, 2007/slides3.ppt |
1.1 MB |
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| videolectures.net/The Analysis of Patterns, Bertinoro 2007/Support Vector Machines and Kernel Methods by Colin Campbell, 2007/1.flv |
167.4 MB |
| videolectures.net/The Analysis of Patterns, Bertinoro 2007/Support Vector Machines and Kernel Methods by Colin Campbell, 2007/2.flv |
137.5 MB |
| videolectures.net/The Analysis of Patterns, Bertinoro 2007/Support Vector Machines and Kernel Methods by Colin Campbell, 2007/slide_descr.txt |
9 KB |
| videolectures.net/The Analysis of Patterns, Bertinoro 2007/Support Vector Machines and Kernel Methods by Colin Campbell, 2007/slides1.pdf |
597 KB |
| videolectures.net/The Analysis of Patterns, Bertinoro 2007/Support Vector Machines and Kernel Methods by Colin Campbell, 2007/slides2.pdf |
808 KB |
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