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|Nov 27 ||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]]
|Nov 27 ||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]]
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|Nov 27 ||Ali Sarhadi|| ||Learning Fast Approximations of Sparse Coding|| ||
|Nov 27 ||Ali Sarhadi|| ||Deep Neural Nets as a Method for Quantitative Structure−Activity Relationships||file:///C:/Users/User/Desktop/Mohsen/deepQSARJChemInfModel2015.pdf||
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|Dec 4 || Chris Choi || || On the difficulty of training recurrent neural networks || [http://www.jmlr.org/proceedings/papers/v28/pascanu13.pdf Paper] || [[On the difficulty of training recurrent neural networks | Summary]]
|Dec 4 || Chris Choi || || On the difficulty of training recurrent neural networks || [http://www.jmlr.org/proceedings/papers/v28/pascanu13.pdf Paper] || [[On the difficulty of training recurrent neural networks | Summary]]

Revision as of 16:12, 30 October 2015

List of Papers

Record your contributions here:

Use the following notations:

S: You have written a summary on the paper

T: You had technical contribution on a paper (excluding the paper that you present from set A or critique from set B)

E: You had editorial contribution on a paper (excluding the paper that you present from set A or critique from set B)

Your feedback on presentations


Set A

Date Name Paper number Title Link to the paper Link to the summary
Oct 16 pascal poupart Guest Lecturer
Oct 16 pascal poupart Guest Lecturer
Oct 23 Ali Ghodsi Lecturer
Oct 23 Ali Ghodsi Lecturer
Oct 23 Ri Wang Sequence to sequence learning with neural networks. Paper Summary
Oct 23 Deepak Rishi Parsing natural scenes and natural language with recursive neural networks Paper Summary
Oct 30 Ali Ghodsi Lecturer
Oct 30 Ali Ghodsi Lecturer
Oct 30 Rui Qiao Going deeper with convolutions Paper Summary
Oct 30 Amirreza Lashkari 21 Overfeat: integrated recognition, localization and detection using convolutional networks. Paper Summary
Mkeup Class (TBA) Peter Blouw Memory Networks. [1] Summary
Nov 6 Ali Ghodsi Lecturer
Nov 6 Ali Ghodsi Lecturer
Nov 6 Anthony Caterini 56 Human-level control through deep reinforcement learning Paper Summary
Nov 6 Sean Aubin Learning Hierarchical Features for Scene Labeling Paper Summary
Nov 13 Mike Hynes 12 Speech recognition with deep recurrent neural networks Paper Summary
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 20 Ali Mahdipour The human splicing code reveals new insights into the genetic determinants of disease 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
Nov 27 Ali Sarhadi Deep Neural Nets as a Method for Quantitative Structure−Activity Relationships file:///C:/Users/User/Desktop/Mohsen/deepQSARJChemInfModel2015.pdf
Dec 4 Chris Choi On the difficulty of training recurrent neural networks Paper Summary
Dec 4 Fatemeh Karimi MULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION Paper
Dec 4 Jan Gosmann A fast learning algorithm for deep belief nets Paper Summary
Dec 4 Dylan Drover Towards AI-complete question answering: a set of prerequisite toy tasks Paper

Set B

Name Paper number Title Link to the paper Link to the summary
Anthony Caterini 15 The Manifold Tangent Classifier Paper
Jan Gosmann Neural Turing machines Paper
Brent Komer Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Paper
Sean Aubin Semi-Supervised Learning with Deep Generative Models Paper
Peter Blouw Generating text with recurrent neural networks Paper