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Final Project Presentations

Lecture 19 (12/1/15, Tuesday)

1. lukedeo / alainez: Sequential CNNs for Multi-Sentence Text Classification
2. yuyan1: Tracking disease progression in radiology reports
3. cwind / xiaoshiw / danyangw: Machine Comprehension using Feature Engineering
4. sjtang / hanjiang: Pruning Deep Recurrent Neural Networks
5. yetian1 / jiyue: Let Computers Do Reading Comprehension
6. nihit / truongk / rgupta9: Predicting success on Kickstarter
7. ekyauk / aacharya / emjtang: Acoustic Cues in Bilingual Speakers
8. arastogi: Context Encoding LSTM
9. justinkk: Video games for annotating NLI data
10. dmg1 / bstate: The Language of Experts
11. justinfu / dthirman: Medical Record Understanding
12. yilunw: Understanding Personality through Social Media
13. mrpeters / ulmerb / matthew0: Literary Social Network Analysis
14. asax / dmoore2: Adversarial Examples for NLP
15. danae: Measuring the Web's Dark Matter
16. sjtodd: Measuring Functional Load with Word Vectors

Lecture 20 (12/3/15, Thursday)

1. onkursen / icaswell / anie: Applying Adversarial Examples to Neural Language Modeling
2. abisee: Exploiting Redundancy in Neural Machine Translation
3. naveen67 / rshu15: Annotation for Word Sense Disambiguation
4. viswa / sameepb: Editing Behavior on Kickstarter
5. tstand: Neural Word Sense Disambiguation
6. klopyrev: Generating News Headlines with RNNs
7. telin / dahuang: AI-Complete Question Answering After Automated Comprehendly Reading
8. agong / jenylu: Picking out Good Dishes from Yelp
9. ajchin / epatters: Extracting Family Trees from Literary Texts
10. jaycaz / martinam / cdixit: Large Scale Language Classification
11. qiaojing / wyixin: Machine Comprehension using Syntactic Features
12. lmurata: An Attempt to Beat the Turing Test
13. vishesh: Alignment Trees
14. aalifimoff / jli14: Abstractive Summarisation with Neural Networks