Spring 2018 Reading Schedule

Reading Schedule for Spring 2018

Presenters: It will be helpful if you can do a 5 min primer of all the new terms in the paper you are presenting.

Readers: Please scroll down for supplementary reading materials suggested by the respective presenters.

Order	Presenter	Paper	Date	Location
1	John	Distilling a neural network into a soft decision tree	01/26/2018	GS 856
2	Cathy	A causal framework for explaining the predictions of black-box sequence-to-sequence models	02/02/2018	GS 856
3	Andrew	Tagging Ingush + Bootstrapping a dependency parser for Maltese	02/09/2018	GS 856
4	Masha	Deep learning: A critical appraisal	02/16/2018	GS 856
5	Jack	Word translation without parallel data + Unsupervised machine translation using monolingual corpora only	02/23/2018	GS 856
6	Becky	A mention-ranking model for abstract anaphora resolution	03/02/2018	GS 856
7	Adam	The lifted matrix-space model for semantic composition	03/16/2018	GS 856
8	Fan	Neighborhood mixture model for knowledge base completion	03/23/2018	GS 856
9	Ajay	Semi-supervised learning with ladder networks + Mean teachers are better role models	03/30/2018	GS 856
10	Enrique	A unified approach to interpreting model predictions	04/06/2018	GS 856
11	Dongfang	Attention is all you need	04/13/2018	GS 856
12	Nick	All that is English may be Hindi	04/20/2018	GS 856
13	Mithun	Extracting automata from recurrent neural networks using queries and counterexamples	04/27/2018	GS 856

Supplementary Materials

Below is a list of any important related resources that the presenter has asked to be made available to the reading group.

Order	Presenter	Additional Resources	Date
4	Masha	blog: In defense of skepticism about deep learning	02/16/2018
9	Ajay	blog: Semi-supervised image classification explained	03/30/2018
11	Dongfang	blog: The Transformer – Attention is all you need	04/13/2018