Fall 2016 Reading Schedule

Reading Schedule for Fall 2016

Order	Presenter	Paper	Date	Location
1	Mihai Surdeanu	Representing Text for Joint Embedding of Text and Knowledge Bases	9/2/2016	GS 906
2	Carlos Scheidegger	Visualizing and Understanding Recurrent Networks Visualizing and Understanding Neural Models in NLP	9/9/2016	GS 906
3	Michael Capizzi	"Why Should I Trust You?": Explaining the Predictions of Any Classifier	9/16/2016	GS 906
4	Dane Bell	On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation Explaining Predictions of Non-Linear Classifiers in NLP	9/23/2016	GS 906
5	Clay Morrison	Deep Reinforcement Learning tutorial 1 Deep Reinforcement Learning tutorial 2 Playing Atari with Deep Reinforcement Learning	9/30/2016	GS 906
6	Steven Bethard	Deep Unordered Composition Rivals Syntactic Methods for Text Classification	10/7/2016	GS 906
7	Marco Valenzuela-Escarcega	Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning	10/14/2016	GS 906
8	Adam King	Word Sense Disambiguation with Neural Language Models	10/21/2016	GS 906
9	Gus Hahn-Powell	Improving Hypernymy Detection with an Integrated Path-based and Distributional Method	10/28/2016	GS 906
10	Heather Lent	Toward Future Scenario Generation: Extracting Event Causality Exploiting Semantic Relation, Context, and Association Features	11/4/2016	GS 906
11	----	Memorial Day	11/11/2016	---
12	Becky Sharp	Easy Questions First? A Case Study on Curriculum Learning for Question Answering	11/18/2016	GS 906
13	Robert Henderson	Harnessing Deep Neural Networks with Logic Rules	12/2/2016	GS 906

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
10	Heather Lent	Supplementary Notes	11/4/2016
12	Becky Sharp	Models used in the paper	11/18/2016