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|Oct 16 ||pascal poupart || ||Guest Lecturer |||| | |Oct 16 ||pascal poupart || ||Guest Lecturer |||| | ||
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|Oct 23 || || || |||| | |Oct 23 || Mike Hynes || ||Speech recognition with deep recurrent neural networks || [http://www.cs.toronto.edu/~fritz/absps/RNN13.pdf Paper] || | ||
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|Oct 23 || Deepak Rishi || || Parsing natural scenes and natural language with recursive neural networks || [http://www-nlp.stanford.edu/pubs/SocherLinNgManning_ICML2011.pdf Paper] || | |Oct 23 || Deepak Rishi || || Parsing natural scenes and natural language with recursive neural networks || [http://www-nlp.stanford.edu/pubs/SocherLinNgManning_ICML2011.pdf Paper] || |
Revision as of 14:53, 5 October 2015
Date | Name | Paper number | Title | Link to the paper | Link to the summary |
Example | Ali Ghodsi | 1 | Deep sparse rectifier neural networks. | Paper | Summary |
Oct 16 | pascal poupart | Guest Lecturer | |||
Oct 16 | pascal poupart | Guest Lecturer | |||
Oct 23 | Mike Hynes | Speech recognition with deep recurrent neural networks | Paper | ||
Oct 23 | Deepak Rishi | Parsing natural scenes and natural language with recursive neural networks | Paper | ||
Oct 30 | Rui Qiao | Going deeper with convolutions | Paper | Summary | |
Oct 30 | Amirreza Lashkari | Overfeat: integrated recognition, localization and detection using convolutional networks. | Paper | Summary | |
Nov 6 | Anthony Caterini | Human-level control through deep reinforcement learning | Paper | Summary | |
Nov 6 | Sean Aubin | Learning Hierarchical Features for Scene Labeling | Paper | Summary | |
Nov 6 | |||||
Nov 13 | Tim Tse | . From machine learning to machine reasoning. Mach. Learn. | Paper | ||
Nov 13 | Maysum Panju | Neural machine translation by jointly learning to align and translate | Paper | ||
Nov 13 | Abdullah Rashwan | Deep neural networks for acoustic modeling in speech recognition. | paper | ||
Nov 20 | Valerie Platsko | Natural language processing (almost) from scratch. | Paper | ||
Nov 20 | Brent Komer | Show, Attend and Tell: Neural Image Caption Generation with Visual Attention | Paper | Summary | |
Nov 20 | Luyao Ruan | Dropout: A Simple Way to Prevent Neural Networks from Overfitting | Paper | ||
Nov 27 | Mahmood Gohari | Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships | Paper | ||
Nov 27 | Derek Latremouille | The Wake-Sleep Algorithm for Unsupervised Neural Networks | Paper | ||
Nov 27 | Xinran Liu | ImageNet Classification with Deep Convolutional Neural Networks | Paper | Summary | |
Dec 4 | Chris Choi | On the difficulty of training recurrent neural networks | Paper | Summary | |
Dec 4 | Fatemeh Karimi | Connectomic reconstruction of the inner plexiform layer in the mouse retina | Paper | ||
Dec 4 | Jan Gosmann | A fast learning algorithm for deep belief nets | Paper | Summary |