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Deep Learning and Unsupervised Feature Learning Workshop --- NIPS 2010

Deep Learning and Unsupervised Feature Learning Workshop a workshop in conjunction with 24th Annual Conference on Neural Information Processing Systems (NIPS 2010) Friday December 10, 2010  Whistler, BC, Canada Schedule available here. Overview In recent years, there has  been a lot  of interest in algorithms that learn  feature hierarchies  from unlabeled  data. Deep learning methods…

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Deep Learning and Unsupervised Feature Learning Workshop --- NIPS 2010 | deeplearningworkshopnips2010.wordpress.com Reviews
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Deep Learning and Unsupervised Feature Learning Workshop a workshop in conjunction with 24th Annual Conference on Neural Information Processing Systems (NIPS 2010) Friday December 10, 2010  Whistler, BC, Canada Schedule available here. Overview In recent years, there has  been a lot  of interest in algorithms that learn  feature hierarchies  from unlabeled  data. Deep learning methods…
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Deep Learning and Unsupervised Feature Learning Workshop --- NIPS 2010 | deeplearningworkshopnips2010.wordpress.com Reviews

https://deeplearningworkshopnips2010.wordpress.com

Deep Learning and Unsupervised Feature Learning Workshop a workshop in conjunction with 24th Annual Conference on Neural Information Processing Systems (NIPS 2010) Friday December 10, 2010  Whistler, BC, Canada Schedule available here. Overview In recent years, there has  been a lot  of interest in algorithms that learn  feature hierarchies  from unlabeled  data. Deep learning methods…

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Schedule | Deep Learning and Unsupervised Feature Learning Workshop --- NIPS 2010

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Deep Learning and Unsupervised Feature Learning Workshop — NIPS 2010. Friday December 10, 2010, Whistler BC. The list of accepted papers can be found here. Tutorial on deep learning and unsupervised feature learning:. Part I: Unsupervised Learning. Part II: Deep Learning. Large-scale image recognition via unsupervised feature learning. Spotlights of Poster Presentations. Poster Session 1 and Group Discussion. 330pm-6.30pm Afternoon Session:. Rich representations for learning visual recognition.

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Deep Learning and Unsupervised Feature Learning Workshop --- NIPS 2010

https://deeplearningworkshopnips2010.wordpress.com/cfp/pcmembers

Deep Learning and Unsupervised Feature Learning Workshop — NIPS 2010. Laurens van der Maaten. Blog at WordPress.com. Follow “Deep Learning and Unsupervised Feature Learning Workshop - - NIPS 2010”. Get every new post delivered to your Inbox. Build a website with WordPress.com.

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Marc'Aurelio Ranzato's home page

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Ranzato [AT] cs [DOT] toronto [DOT] edu. I am currently a research scientist at the Facebook AI Research lab in Menlo Park CA. I previously worked at Google in the Brain team, and before that, I was a post-doctoral fellow in Machine Learning, University of Toronto. I worked in Geoffrey Hinton's lab for two wonderful years. I did my Ph.D. in Computer Science at New York University in Yann LeCun's group. I am originally from Padova in Italy, where I graduated in Electronics Engineering. CVPR 2014 tutorial ...

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Redefining Open Minds: 12/01/2012 - 01/01/2013

http://jbhuang0604.blogspot.com/2012_12_01_archive.html

Wednesday, December 26, 2012. Demonstration of Forced Perspective. I found two excellent demonstration videos of forced perspective. The first one is by Richard Wiseman. He demonstrated how to use optical illusion to make objects appear smaller or larger than they actually are. Photographers also use this trick to create context in their photos. See What makes a creative photograph. The second one comes from. What Makes a Creative Photograph? Posted by Jia-Bin Huang. Saturday, December 22, 2012. This is ...

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Deep Learning and Unsupervised Feature Learning Workshop --- NIPS 2010

Deep Learning and Unsupervised Feature Learning Workshop — NIPS 2010. And Unsupervised Feature Learning. A workshop in conjunction with. 24th Annual Conference on Neural Information Processing Systems (NIPS 2010). Friday December 10, 2010 Whistler, BC, Canada. In recent years, there has been a lot of interest in algorithms that. Learn feature hierarchies from unlabeled data. Deep learning. Methods such as deep belief networks, sparse coding-based methods,. The organizing committee as well as by prominent...

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