f17Stat946PaperSignUp

Record your contributions here:

Use the following notations:

P: You have written a summary/critique on the paper.

T: You had a technical contribution on a paper (excluding the paper that you present).

E: You had an editorial contribution on a paper (excluding the paper that you present).

Your feedback on presentations

Paper presentation

Date	Name	Paper number	Title	Link to the paper	Link to the summary
Oct 12 (example)	Ri Wang		Sequence to sequence learning with neural networks.	Paper	Summary
Oct 24	Sakif Khan	1	Improved Variational Inference with Inverse Autoregressive Flow	[1]	[2]
Oct 24		2
Oct 24		3
Oct 26		4
Oct 26		5
Oct 26		6
Oct 31
Oct 31
Oct 31
Nov 2
Nov 2
Nov 2
Nov 7	Dishant Mittal		meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting	Paper
Nov 7	Yangjie Zhou		An Alternative Softmax Operator for Reinforcement Learning	Paper
Nov 7	Rahul Iyer		Hash Embeddings for Efficient Word Representations	NIPS 2017 Paper
Nov 9	ShuoShuo Liu		Learning the Number of Neurons in Deep Networks	Paper
Nov 9	Aravind Balakrishnan		FeUdal Networks for Hierarchical Reinforcement Learning	[3]
Nov 9	Varshanth R Rao		Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study	Paper
Nov 14	Avinash Prasad		Coupled GAN
Nov 14	Nafseer Kadiyaravida		Dialog-based Language Learning	Paper	Summary
Nov 14
Nov 16	Hamidreza Shahidi		Teaching Machines to Describe Images via Natural Language Feedback
Nov 16	Sachin vernekar		Natural-Parameter Networks: A Class of Probabilistic Neural Networks	Paper	Summary
Nov 16	Yunqing HE		LightRNN: Memory and Computation-Efficient Recurrent Neural Networks	[4]
Nov 21	Aman Jhunjhunwala		Curiosity-driven Exploration by Self-supervised Prediction	Paper	Summary
Nov 21	Peiying Li		Deep Learning without Poor Local Minima	[5]	Summary
Nov 21	Ashish Gaurav		Deep Exploration via Bootstrapped DQN	Paper	Summary
Nov 23	Venkateshwaran Balasubramanian		Large-Scale Evolution of Image Classifiers	Paper
Nov 23	Ershad Banijamali		Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	Paper
Nov 23	Dylan Spicker		Unsupervised Domain Adaptation with Residual Transfer Networks	Paper
Nov 28	Mike Rudd	1	Deep Transfer Learning with Joint Adaptation Networks	Paper	Summary
Nov 28
Nov 28
Nov 30
Nov 30
Nov 30