Skip to content

Latest commit

 

History

History
500 lines (264 loc) · 19 KB

archived-201510-201806.md

File metadata and controls

500 lines (264 loc) · 19 KB

READING GROUP: October 2015 -- June 2018

(converted copy of the page https://www.sheffield.ac.uk/dcs/research/groups/nlp#tab05)

The target audience is all the members of the NLP group and other possible interested participants.

The meeting will take place weekly for one hour usually on Tuesdays from 11-12pm.

The meetings of the group will be informal and no necessary preparation will be required with the exception of the moderator reading the current paper and the rest having at least a brief overview of it.

Next Meeting

Past Meetings

Tuesday 12 June 2018

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

Chelsea Finn, Pieter Abbeel, Sergey Levine, ICML 2017
Blog post about the paper by the authors

Tuesday 10 April 2018

Style Transfer from Non-Parallel Text by Cross-Alignment

Shen, T; Lei, T; Barzilay, R; Jaakola, T.

Tuesday 3 April 2018

Generating Natural Adversarial Examples

Zhengli Zhao, Dheeru Dua and Sameer Singh

Tuesday 20 February 2018

ACL Paper submission feedback session

Tuesday 13 February 2018

Unbounded cache model for online language modeling with open vocabulary

Edouard Grave, Moustapha Cisse & Armand Joulin

Tuesday 6 February 2018

Neural Sequence Learning Models for Word Sense Disambiguation

Alessandro Raganato, Claudio Delli Bovi & Roberto Navigli

Tuesday 30 January 2018

End-to-End Differentiable Proving

Tim Rocktäschel & Sebastian Riedel

Tuesday 23 January 2018

Unsupervised Learning of Universal Sentence Representations from NLI Data.

Tuesday 28 November 2017

Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

Melvin Johnson, Mike Schuster, Quoc V. Le, et al.

Tuesday 14 November 2017

Representations of language in a model of visually grounded speech signal

Grzegorz Chrupała, Lieke Gelderloos & Afra Alishahi

Tuesday 7 November 2017

A Class of Submodular Functions for Document Summarization

Hui Lin & Jeff Bilmes

Tuesday 31 October 2017

Question Generation for Question Answering

Nan Duan, Duyu Tang, Peng Chen & Ming Zhou

Tuesday 24 October 2017

Morphological Inflection Generation with Hard Monotonic Attention

Roee Aharoni & Yoav Goldberg

Tuesday 17 October 2017

A Factored Neural Network Model for Characterizing Online Discussions in Vector Space

Hao Cheng, Hao Fang, Mari Ostendorf

Tuesday 10 October 2017

Understanding Black-box Predictions via Influence Functions

Pang Wei Koh, Percy Liang; Published in Proceedings of International Conference on Machine Learning, 2017

Tuesday 3 October 2017

Zero-Shot Relation Extraction via Reading Comprehension

Omer Levy, Minjoon Seo, Eunsol Choi and Luke Zettlemoyer

Tuesday 19 September 2017

"Men also like shopping: Reducing Gender Bias Amplification Using Corpus Level Constraints"

Tuesday 29 August 2017

Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction

Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell

Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3309-3318, 2017.

Tuesday 22 August 2017

Split and Rephrase, Accepted for EMNLP 2017

Shashi Narayan, Claire Gardent, Shay B. Cohen and Anastasia Shimorina

Tuesday 15 August 2017

Attention Is All You need
A new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely

Tuesday 8 August 2017

Learning to Compute Word Embeddings On the Fly

Dzmitry Bahdanau, Tom Bosc, Stanisław Jastrzębski, Edward Grefenstette, Pascal Vincent, Yoshua Bengio

Tuesday 1 August 2017

Learning to Generate Textual Data, EMNLP 2016
Guillaume Bouchard and Pontus Stenetorp and Sebastian Riedel

Tuesday 11 July 2017

SoundNet: Learning Sound Representations from Unlabeled Video

Yusuf Aytar, Carl Vondrick, Antonio Torralba

Tuesday 4 July 2017

Sentence Simplification with Deep Reinforcement Learning

Xingxing Zhang, Mirella Lapata

Tuesday 27 June 2017

Generation and Comprehension of Unambiguous Object Descriptions

Junhua Mao, Jonathan Huang, Alexander Toshev, Oana Camburu, Alan Yuille, Kevin Murphy

Tuesday 20 June 2017

Understanding the BPE algorithm

Tuesday 13 June 2017

Sequence-to-Sequence Models Can Directly Transcribe Foreign Speech

Ron J. Weiss, Jan Chorowski, Navdeep Jaitly, Yonghui Wu, Zhifeng Chen

Tuesday 6 June 2017

Covonlutional Sequence to Sequence Learning

Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin

Tuesday 30 May 2017

Program Induction by Rationale Generation:Learning to Solve and Explain Algebraic Word Problems

Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom

Tuesday 9 May 2017

Chatterjee et al.: Online Automatic Post-editing for MT in a Multi-Domain Translation Environment

Tuesday 6 May 2017

Convolutional Sequence to Sequence Learning

Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin

Tuesday 2 May 2017

[Coarse-to-Fine Question Answering for Long Documents](http:// http://homes.cs.washington.edu/~eunsol/papers/acl17eunsol.pdf)

Tuesday 25 April 2017

Re-evaluating Automatic Metrics for Image Captioning

Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis, Erkut Erdem

Tuesday 18 April 2017

Neural Tree Indexers, EACL2017

Tuesday 11 April 2017

EACL Recap

Tuesday 4 April 2017

Shakir Mohammed's deep learning overview

Tuesday 28 March 2017

Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond

Tuesday 21 March 2017

Unsupervised AMR-Dependency Parse Alignment

Tuesday 14 March 2017

Kim et al. (2016): Examples are not Enough, Learn to Criticize! Criticism for Interpretability, NIPS 2016

Tuesday 7 March 2017

Latent Variable Dialogue Models and their Diversity

Kris Cao and Stephen Clark

Tuesday 28 February 2017

Zhang et al. EACL2017

Tuesday 21 February 2017

Structured Attention Networks

Tuesday 14 February 2017

CORE: Context-Aware Open Relation Extraction with Factorization Machines

by Fabio Petroni, Luciano Del Corro and Rainer Gemulla

Tuesday 7 February 2017

Adversarial Training Methods for Semi-Supervised Text Classification

Takeru Miyato, Andrew, M.Dai, Ian Goodfellow

Tuesday 31 January 2017

Learning to Prune: Exploring the Frontier of Fast and Accurate Parsing

Tim Vieira and Jason Eisner

Tuesday 24 January 2017

Matching Networks for One Shot Learning

Oriol Vinyals, Charles Blundell, Tim Lillicrap, Koray Kavukcuoglu, Daan Wierstra

Tuesday 17 January 2017

Learning Structured Predictors from Bandit Feedback for Interactive NLP. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL). Berlin, Germany

Artem Sokolov, Julia Kreutzer, Christopher Lo, Stefan Riezler

Tuesday 13 December 2016

Optimization and Sampling for NLP from a Unified Viewpoint

Marc Dymetman, Guillaume Bouchard, Simon Carter

Tuesday 6 December 2016

Matrix Completion has No Spurious Local Minimum

Rong Ge, Jason D. Lee, Tengyu Ma

Tuesday 29 November 2016

Compositional Semantic Parsing on Semi-Structured Tables 
Panupong Pasupat and Percy Liang

Tuesday 22 November 2016

Minimum Risk Training for Neural Machine Translation 
Shiqi Shen, Yong Cheng, Zhougjun He, Wei He, Hua Wu, Maosong Sun, Yang Liu

Tuesday 15 November 2016

Generation from Abstract Meaning Representation using Tree Transducers 
Jeffrey Flanigan, Chris Dyer, Noah A. Smith and Jaime Carbonell

Tuesday 1 November 2016

Visual Representations for Topic Understanding and Their Effects on Manually Generated Labels Transactions of the Association for Computational Linguistics, 2016. 
Alison Smith, Tak Yeon Lee, Forough Poursabzi-Sangdeh, Leah Findlater, Jordan Boyd-Graber, and Niklas Elmqvist

Tuesday 25 October 2016

Learning to Search Better than your Teacher

Talk 
Chang et al. ICML 2015

Tuesday 11 October 2016

A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task 
Danqi Chen, Jason Bolton, Christopher D. Manning

Tuesday 4 October 2016

Ultradense Word Embeddings by Orthogonal Transformation 
Sascha Rothe, Sebastian Ebert, Hinrich Schütze

Tuesday 7 June 2016

Not All Character N-grams Are Created Equal: A Study in Authorship Attribution. 
Upendra Sapkota, Steven Bethard, Manuel Montes-y-Gómez & Thamar Solorio (2015)

Tuesday 31 May 2016

Relation extraction with matrix factorization and universal schemas.

Riedel, S., Yao, L., McCallum, A., & Marlin, B. M. (2013)

Tuesday 10 May 2016

Training Deterministic Parsers with Non-Deterministic Oracles, TACL

slides 
Goldberg, Y. and Nivre, J. (2013)

Tuesday 3 May 2016

A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing 
Vlachos, A. and Clark, S.

Tuesday 22 April 2016

Sequence Level Training with recurrent Neural Networks 
Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli, Wojciech Zaremba

Tuesday 22 March 2016

"Distributed Representation of Sentences and Documents" 
Quoc Le and Tomas Mikolov

Tuesday 8 March 2016

AutoExtend: Extending Word Embeddings to Embeddings for Synsets and Lexemes 
Sascha Rothe; Hinrich Schütze. ACL2015 (best student paper)

Tuesday 23 February 2016

From Word Embeddings To Document Distances 
Kusner et al.

Tuesday 16 February 2016

"Target-Dependent Twitter Sentiment Classification with Rich Automatic Features"

Tuesday 9 February 2016

"Evaluation methods for unsupervised word embeddings"

Tuesday 25 January 2016

Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks 
Hua He, Kevin Gimpel, and Jimmy Lin. EMNLP2015

Tuesday 19 January 2016

Multilingual Image Description with Neural Sequence Models

Tuesday 12 January 2016

"Improving Distributional Similarity with Lessons Learned from Word Embeddings"

Tuesday 8 December 2015

Using Discourse Structure Improves Machine Translation Evaluation
F Guzmán, S Joty, L Màrquez, P Nakov

And here are the author's slides

Tuesday 1 December 2015

Practical Bayesian Optimization of Machine Learning Algorithms Advances in Neural Information Processing Systems, 2012 
Snoek, J.; Larochelle, H. & Adams, R. P.

Related presentations/lecture slides:

http://becs.aalto.fi/en/research/bayes/courses/4613/Vik_Kamath_Presentation.pdf

http://drona.csa.iisc.ernet.in/~indous/Lectures-2014/slides/jasper.pdf

Related Video

My reading group presentation slides

Tuesday 24 November 2015

Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks ACL 2015 
LSTMs? Kai Sheng Tai, Richard Socher, Christopher D. Manning

http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-2-implementing-a-language-model-rnn-with-python-numpy-and-theano/

http://www.wildml.com/2015/10/recurrent-neural-networks-tutorial-part-3-backpropagation-through-time-and-vanishing-gradients/

http://colah.github.io/posts/2015-08-Understanding-LSTMs/

Additional resource about LSTM: "Anyone Can Learn To Code an LSTM-RNN in Python"

Tuesday 17 November 2015

RNNs/LSTMs ConvNets

More details on auto encoders for unsupervised pre-training:

http://deeplearning.stanford.edu/wiki/index.php/Autoencoders_and_Sparsity

http://www.jmlr.org/papers/volume11/erhan10a/erhan10a.pdf

http://www.slideshare.net/billlangjun/simple-introduction-to-autoencoder

Tuesday 10 November 2015

Multi-Metric Optimization Using Ensemble Tuning. NAACL2013. Video 
Baskaran Sankaran, Anoop Sarkar and Kevin Duh

Tuesday 3 November 2015

NN tutorials by Quoc Le

Josiah's slides

Other resources:

Andrej Karpathy's notes

Different objective functions, multiclass problems

Gradient descent

Backpropagation

Discussion about different activation functions

Tuesday 27 October 2015

Three blog posts introducing RNNs for language modelling in equations and code

might help to read this NLP primer

Additional material:
a thorough explanation of back propagation

Tuesday 20 October 2015

Teaching Machines to Read and Comprehend. NIPS 2015. 
Karl Moritz Hermann, Tomáš Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom

Slides (presented at LXMLS)

Background reading:

Understanding LSTMs

NAACL 2013 Tutorial "Deep Learning without Magic"

EMNLP 2014 Tutorial "Embedding Methods for NLP"

Related Work:

Entailment with Neural Attention (better description of attention models than in the NIPS paper in my opinion)

Memory Networks

Tuesday 13 October 2015

A large annotated corpus for learning natural language inference. Proceedings of EMNLP 2015. 
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning

Should compare this to work on (multilingual) textual similarity