stat946F18: Difference between revisions
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|Feb 15 (example)||Ri Wang || ||Sequence to sequence learning with neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [http://wikicoursenote.com/wiki/Stat946f15/Sequence_to_sequence_learning_with_neural_networks#Long_Short-Term_Memory_Recurrent_Neural_Network Summary] | |Feb 15 (example)||Ri Wang || ||Sequence to sequence learning with neural networks.||[http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf Paper] || [http://wikicoursenote.com/wiki/Stat946f15/Sequence_to_sequence_learning_with_neural_networks#Long_Short-Term_Memory_Recurrent_Neural_Network Summary] | ||
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|Oct 25 || Dhruv Kumar || | |Oct 25 || Dhruv Kumar || 1 || Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs || [https://openreview.net/pdf?id=rkRwGg-0Z Paper] || | ||
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|Oct 25 || Shala Chen || | |Oct 25 || Shala Chen || 2|| || || | ||
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|Oct 25 || Juan Carrillo || | |Oct 25 || Juan Carrillo || 3|| Hierarchical Representations for Efficient Architecture Search || [https://arxiv.org/abs/1711.00436 Paper] || | ||
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|Oct 30 || Manpreet Singh Minhas || 1|| || || | |Oct 30 || Manpreet Singh Minhas || 1|| || || |
Revision as of 20:09, 8 October 2018
Project Proposal
Paper presentation
Date | Name | Paper number | Title | Link to the paper | Link to the summary |
Feb 15 (example) | Ri Wang | Sequence to sequence learning with neural networks. | Paper | Summary | |
Oct 25 | Dhruv Kumar | 1 | Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs | Paper | |
Oct 25 | Shala Chen | 2 | |||
Oct 25 | Juan Carrillo | 3 | Hierarchical Representations for Efficient Architecture Search | Paper | |
Oct 30 | Manpreet Singh Minhas | 1 | |||
Oct 30 | Marvin Pafla | 2 | |||
Oct 30 | Glen Chalatov | 3 | TBD | ||
Oct 30 | Gaurav Sahu | 4 | TBD | ||
Nov 1 | Sriram Ganapathi Subramanian | 1 | Differentiable plasticity: training plastic neural networks with backpropagation | Paper | |
Nov 1 | Hadi Nekoei | 1 | Synthesizing Programs for Images using Reinforced Adversarial Learning | Paper | |
Nov 1 | Henry Chen | 1 | DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks | Paper | |
Nov 1 | Amirpasha Ghabussi | 1 | |||
Nov 6 | Nargess Heydari | 2 | |||
Nov 6 | Aravind Ravi | 3 | |||
Nov 6 | Ronald Feng | ||||
Nov 8 | Neel Bhatt | 1 | [TBD] | ||
Nov 8 | Jacob Manuel | 2 | |||
Nov 8 | Charupriya Sharma | 2 | |||
NOv 13 | Sagar Rajendran | 1 | Zero-Shot Visual Imitation | Paper | |
Nov 13 | Jiazhen Chen | 2 | |||
Nov 13 | Neil Budnarain | 2 | PixelNN: Example-Based Image Synthesis | Paper | |
Nov 13 | Kashif Khan | 2 | |||
NOv 15 | Zheng Ma | 3 | Reinforcement Learning of Theorem Proving | Paper | |
Nov 15 | Abdul Khader Naik | 4 | |||
Nov 15 | Johra Muhammad Moosa | 2 | |||
Nov 20 | Ki Beom Lee | ||||
NOv 20 | Zahra Rezapour Siahgourabi | 19 | |||
Nov 20 | Shubham Koundinya | 6 | |||
Nov 20 | Salman Khan | Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples | paper | ||
NOv 22 | Soroush Ameli | 22 | |||
Nov 22 | Ivan Li | 23 | Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate | Paper | |
Nov 22 | Sigeng Chen | 2 | |||
Nov 27 | Aileen Li | 8 | Spatially Transformed Adversarial Examples | Paper | |
NOv 27 | Xudong Peng | 9 | |||
Nov 27 | Xinyue Zhang | 10 | An Inference-Based Policy Gradient Method for Learning Options | Paper | |
NOv 29 | Junyi Zhang | 11 | |||
Nov 29 | Travis Bender | 12 | Automatic Goal Generation for Reinforcement Learning Agents | Paper | |
Nov 29 | Patrick Li | 12 | Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices | Paper | |
Nov 29 | Ahmed Afify | 13 | Don't Decay the Learning Rate, Increase the Batch Size | Paper |