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|Nov 6 ||  Aravind Ravi || 3 || ||  ||  
|Nov 6 ||  Aravind Ravi || 3 || ||  ||  
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|Nov 6 || Ki Beom Lee ||  || || ||
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|Nov 6 ||  Ronald Feng ||  || ||  ||  
|Nov 6 ||  Ronald Feng ||  || ||  ||  
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|Nov 15 || Johra Muhammad Moosa  || 2||  ||  ||  
|Nov 15 || Johra Muhammad Moosa  || 2||  ||  ||  
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|Nov 20 || Ki Beom Lee ||  || || ||
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|NOv 20 || Zahra Rezapour Siahgourabi  || 19||  ||  ||  
|NOv 20 || Zahra Rezapour Siahgourabi  || 19||  ||  ||  

Revision as of 12:56, 7 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 2 TBD
Oct 25 Shala Chen 3
Oct 25 Juan Carrillo 4
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