f15Stat946PaperSignUp: Difference between revisions

Revision as of 14:56, 2 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
Oct 23
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 13	Xinran Liu		ImageNet Classification with Deep Convolutional Neural Networks	Paper	Summary
Nov 13
Nov 20	Valerie Platsko		Natural language processing (almost) from scratch.	Paper
Nov 20	Brent Komer		Convolutional Neural Network-based Place Recognition	Paper	Summary
Nov 27	Mahmood Gohari		Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships	Paper
Nov 27
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

@@ Line 30: / Line 30: @@
 |Nov 6 || Anthony Caterini || || Human-level control through deep reinforcement learning ||[http://www.nature.com/nature/journal/v518/n7540/pdf/nature14236.pdf Paper]|| [[Human-level control through deep reinforcement learning|Summary]]
 |-
-|Nov 6 || Sean Aubin || || Learning Hierarchical Features
+|Nov 6 || Sean Aubin || ||Learning Hierarchical Features for Scene Labeling ||[http://yann.lecun.com/exdb/publis/pdf/farabet-pami-13.pdf Paper]||[[Learning Hierarchical Features for Scene Labeling|Summary]]
-for Scene Labeling || http://yann.lecun.com/exdb/publis/pdf/farabet-pami-13.pdf ||
 |-
 |Nov 13 ||Xinran Liu || ||ImageNet Classification with Deep Convolutional Neural Networks ||[http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf Paper]||[[ImageNet Classification with Deep Convolutional Neural Networks|Summary]]