ÚFAL Reading Group
A deep learning reading group.
ÚFAL RG in 2016
ÚFAL Reading Group is focused on Machine Learning in NLP.
If you are interested sign up to our mailing list.
Regular meetings take place on Tuesday at 14:00 in S1.
Program
| Date | Who | Title | Link |
|---|---|---|---|
| 04 Oct 2016 | Milan Straka | Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton: Layer Normalization | https://arxiv.org/abs/1607.06450 |
| 11 Oct 2016 | Aleš Tamchyna | Shiqi Shen et al: Minimum Risk Training for Neural Machine Translation | https://arxiv.org/abs/1512.02433 |
| 18 Oct 2016 | Milan Straka | Sam Wiseman, Alexander M. Rush: Sequence-to-Sequence Learning as Beam-Search Optimization | https://arxiv.org/abs/1606.02960 |
| 25 Oct 2016 | Ondřej Plátek | Bahdanau et al: An Actor-Critic Algorithm for Sequence Prediction | https://arxiv.org/abs/1607.07086 |
| 01 Nov 2016 | Petr Bělohlávek | Dumoulin, Belghazi et al: Adversarially Learned Inference | https://arxiv.org/abs/1606.00704 |
| 08 Nov 2016 | No RG | Dean's sports day | |
| 15 Nov 2016 | Rudolf Rosa | Bojanowski et al: Enriching Word Vectors with Subword Information | https://arxiv.org/abs/1607.04606 |
| 22 Nov 2016 | Martin Popel | Jan Chorowski, Michał Zapotoczny, Paweł Rychlikowski: Read, Tag, and Parse All at Once, or Fully-neural Dependency Parsing | https://arxiv.org/abs/1609.03441 |
| 29 Nov 2016 | Vojtěch Hudeček | Adam Santoro et al: One-shot Learning with Memory-Augmented Neural Networks | https://arxiv.org/abs/1605.06065 |
| 06 Dec 2016 | David Mareček | Omer Levy, Anders Søgaard, Yoav Goldberg: Reconsidering Cross-lingual Word Embeddings | https://arxiv.org/abs/1608.05426 |
| 13 Dec 2016 | Jindřich Libovický | Jiasen Lu, Caiming Xiong, Devi Parikh and Richard Socher: Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning | https://arxiv.org/abs/1612.01887 |
| 20 Dec 2016 | Dušan Variš | Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber: Training Very Deep Networks | https://arxiv.org/abs/1507.06228 |
| 03 Jan 2017 | No RG | You can visit a talk at 1pm in SU1: Memory Networks for Question Answering by Jakub Hajič | |
| 10 Jan 2017 | Milan Straka | Diederik P Kingma, Max Welling: Auto-Encoding Variational Bayes | https://arxiv.org/abs/1312.6114 |
| Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, Samy Bengio: Generating Sentences from a Continuous Space | https://arxiv.org/abs/1511.06349 |
Papers for Inspiration
You can choose any paper you find interesting, but if you would like some inspiration, you can look here:
Word Embeddings
- Tolga Bolukbasi, Kai-Wei Chang, James Zou, Venkatesh Saligrama, Adam Kalai: Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. https://arxiv.org/abs/1607.06520
- Omer Levy, Anders Søgaard, Yoav Goldberg: Reconsidering Cross-lingual Word Embeddings. https://arxiv.org/abs/1608.05426
Parsing
- Eliyahu Kiperwasser, Yoav Goldberg: Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations. https://arxiv.org/abs/1603.04351
- Yuan Zhang, David Weiss: Stack-propagation: Improved Representation Learning for Syntax. https://arxiv.org/abs/1603.06598
- Bernd Bohnet, Ryan McDonald, Emily Pitler and Ji Ma: Generalized Transition-based Dependency Parsing via Control Parameters. https://www.aclweb.org/anthology/P/P16/P16-1015.pdf
Neural Machine Translation
- Rico Sennrich, Barry Haddow, Alexandra Birch: Edinburgh Neural Machine Translation Systems for WMT 16. https://arxiv.org/abs/1606.02891
- Yonghui Wu et al.: Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. https://arxiv.org/abs/1609.08144
Language Correction
- Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, Andrew Y. Ng: Neural Language Correction with Character-Based Attention. https://arxiv.org/abs/1603.09727
Language Modelling
- Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, Yonghui Wu: Exploring the Limits of Language Modeling. https://arxiv.org/abs/1602.02410
Image Labelling
- Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan: Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge. https://arxiv.org/abs/1609.06647
Network Architectures
- Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber: Training Very Deep Networks. https://arxiv.org/abs/1507.06228
- Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutník, Jürgen Schmidhuber: Recurrent Highway Networks. https://arxiv.org/abs/1607.03474
Structured Prediction
- Daniel Andor, Chris Alberti, David Weiss, Aliaksei Severyn, Alessandro Presta, Kuzman Ganchev, Slav Petrov, Michael Collins: Globally Normalized Transition-Based Neural Networks. https://arxiv.org/abs/1603.06042
- Sam Wiseman, Alexander M. Rush: Sequence-to-Sequence Learning as Beam-Search Optimization. https://arxiv.org/abs/1606.02960
Variational Autoencoders
- Diederik P Kingma, Max Welling: Auto-Encoding Variational Bayes. https://arxiv.org/abs/1312.6114
- Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, Samy Bengio: Generating Sentences from a Continuous Space. https://arxiv.org/abs/1511.06349
Speech Synthesis
- Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, Koray Kavukcuoglu: WaveNet: A Generative Model for Raw Audio. https://arxiv.org/abs/1609.03499