Revision as of 10:35, 4 October 2018

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		1
Oct 25		2
Oct 25		3
Oct 30	Manpreet Singh Minhas	1
Oct 30	Marvin Pafla	2
Nov 1	Sriram Ganapathi Subramanian	1	Mean Field Multi-Agent Reinforcement Learning	Paper
Nov 1	Hadi Nekoei	1
Nov 1	Henry Chen	1	DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks	Paper
Nov 6	Nargess Heydari	2
Nov 6	Aravind Ravi	3
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
NOv 15	Zheng Ma	3	Reinforcement Learning of Theorem Proving	Paper
Nov 15	Abdul Khader Naik	4
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	A Distributional Perspective on Reinforcement Learning	Paper
NOv 29	Junyi Zhang	11
Nov 29	Travis Bender	12	Automatic Goal Generation for Reinforcement Learning Agents	Paper

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 |Nov 1 ||  Hadi Nekoei || 1||  ||   ||
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+|Nov 1 ||  Henry Chen || 1|| DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks || [https://ieeexplore.ieee.org/abstract/document/7989236 Paper] ||
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 |Nov 6 ||  Nargess Heydari || 2 || ||  ||