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Record your contributions here [1]

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).

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

Summary Slides

Oct 25

Amirpasha Ghabussi

2

DCN+: Mixed Objective And Deep Residual Coattention for Question Answering

Paper

Summary

Oct 25

Juan Carrillo

3

Hierarchical Representations for Efficient Architecture Search

Paper

Summary Slides

Oct 30

Manpreet Singh Minhas

4

End-to-end Active Object Tracking via Reinforcement Learning

Paper

Summary

Oct 30

Marvin Pafla

5

Fairness Without Demographics in Repeated Loss Minimization

Paper

Summary

Oct 30

Glen Chalatov

6

Pixels to Graphs by Associative Embedding

Paper

Summary

Nov 1

Sriram Ganapathi Subramanian

7

Differentiable plasticity: training plastic neural networks with backpropagation

Paper

Summary Slides

Nov 1

Hadi Nekoei

8

Synthesizing Programs for Images using Reinforced Adversarial Learning

Paper

Summary Slides

Nov 1

Henry Chen

9

DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks

Paper

Summary Slides

Nov 6

Nargess Heydari

10

Wavelet Pooling For Convolutional Neural Networks Networks

Paper

Summary Slides

Nov 6

Aravind Ravi

11

Towards Image Understanding from Deep Compression Without Decoding

Paper

Summary Slides

Nov 6

Ronald Feng

12

Learning to Teach

Paper

Summary Slides

Nov 8

Neel Bhatt

13

Annotating Object Instances with a Polygon-RNN

Paper

Summary Slides

Nov 8

Jacob Manuel

14

Co-teaching: Robust Training Deep Neural Networks with Extremely Noisy Labels

Paper

Summary Slides

Nov 8

Charupriya Sharma

15

A Bayesian Perspective on Generalization and Stochastic Gradient Descent

Paper

Summary

NOv 13

Sagar Rajendran

16

Zero-Shot Visual Imitation

Paper

Summary

Nov 13

Ruijie Zhang

17

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction

Paper

Summary

Nov 13

Neil Budnarain

18

Predicting Floor Level For 911 Calls with Neural Networks and Smartphone Sensor Data

Paper

Summary

NOv 15

Zheng Ma

19

Reinforcement Learning of Theorem Proving

Paper

Nov 15

Abdul Khader Naik

20

Multi-View Data Generation Without View Supervision

Paper

Summary

Nov 15

Johra Muhammad Moosa

21

Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin

Paper

Summary

NOv 20

Zahra Rezapour Siahgourabi

22

Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias

Paper

Nov 20

Shubham Koundinya

23

Countering Adversarial Images Using Input Transformations

Nov 20

Salman Khan

24

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

paper

NOv 22

Soroush Ameli

25

Learning to Navigate in Cities Without a Map

paper

Nov 22

Ivan Li

26

Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction

Paper

Nov 22

Sigeng Chen

27

Nov 27

Aileen Li

28

Spatially Transformed Adversarial Examples

Paper

Nov 27

Xudong Peng

29

DropBlock: A regularization method for convolutional networks

Paper

Nov 27

Xinyue Zhang

30

An Inference-Based Policy Gradient Method for Learning Options

Paper

NOv 29

Junyi Zhang

31

Autoregressive Convolutional Neural Networks for Asynchronous Time Series

Paper

Nov 29

Travis Bender

32

Automatic Goal Generation for Reinforcement Learning Agents

Paper

Nov 29

Patrick Li

33

Matrix Capsules with EM Routing

Paper

Makeup

Jiazhen Chen

34

Makeup

Gaurav Sahu

36

TBD

Makeup

Kashif Khan

37

Wasserstein Auto-Encoders

Paper

Makeup

Shala Chen

38

A NEURAL REPRESENTATION OF SKETCH DRAWINGS

Makeup

Ki Beom Lee

39

Detecting Statistical Interactions from Neural Network Weights

Paper

Makeup

Wesley Fisher

40

Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling

Paper

Summary

30-Nov

Ahmed Afify

35

Don't Decay the Learning Rate, Increase the Batch Size

Paper