NEW: Advanced NMT is offered in SS 2016, click here.
Neural Machine Translation (NMT) is a new paradigm in data-driven machine translation. Previous generation Statistical Machine Translation (SMT) systems are built using a collection of heuristic models, typically combined in a log-linear model with a small number of parameters. In Neural Machine Translation, the entire translation process is posed as an end-to-end supervised classification problem, where the training data is pairs of sentences. While in SMT systems, word-alignment is carried out, and then fixed, and then various sub-models are estimated from the word-aligned data, this is not the case in NMT. In NMT, fixed word-alignments are not used, and instead the full sequence to sequence task is handled in one model.
Here is a link to last semester's seminar.
NEW: David Kaumanns is also organizing a Munich interest group for Deep Learning, which has an associated mailing list. See the link here: http://www.cis.uni-muenchen.de/~davidk/deep-munich/
Email Address: SubstituteLastName@cis.uni-muenchen.de
CIS, LMU Munich
NEW TIME: 14:30 (was 14:00 before)!!!
Thursdays 14:30 s.t., location is C105 (CIS Besprechungsraum).
Click here for directions to CIS.
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|Thursday, November 5th||Y Bengio, R Ducharme, P Vincent (2003). A neural probabilistic language model. Journal of Machine Learning Research 3, 1137-1155||Helmut Schmid|
|Thursday, November 12th||Sundermeyer, M.; Schlüter, R. & Ney, H (2012). LSTM Neural Networks for Language Modeling. Interspeech||David Kaumanns|
|Thursday, November 19th||Graves, Alex (2014). Generating Sequences With Recurrent Neural Networks. Neural and Evolutionary Computing||link||Alex Fraser|
|Thursday, November 26th||Kalchbrenner, Nal, Phil Blunsom (2013). Recurrent Continuous Translation Models. EMNLP.||Usama Yaseen|
|Thursday, December 3rd||Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio (2014). Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. EMNLP||link||Ales Tamchyna|
|Thursday, December 10th||Sutskever, Ilya, Oriol Vinyals, and Quoc V Le (2014). Sequence to sequence learning with neural networks. Advances in Neural Information Processing Systems.||link||Stefan Gerdjikov|
|Thursday, December 17th||Presentation on Exploding Gradient (no reading but see: Hochreiter, Schmidhuber: Long Short-Term Memory, Neural Computation 9(8):1735-1780, 1997. Sections 3 and 4)||Christian Meyer|
|Thursday, January 14th||Bahdanau, Dzmitry, Kyunghyun Cho, Yoshua Bengio (2015). Neural Machine Translation by Jointly Learning to Align and Translate. ICLR.||link||Helmut Schmid|
|Thursday, January 28th||Yaming Sun et al (2015). Modeling Mention, Context and Entity with Neural Networks for Entity Disambiguation. IJCAI.||Yadollah Yaghoobzadeh|
|Thursday, February 4th||Jean, Sébastien, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio (2015). On Using Very Large Target Vocabulary for Neural Machine Translation.||link||Tsuyoshi Okita|
|Thursday, February 18th||Gulcehre, Caglar, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Loic Barrault, Huei-Chi Lin, Fethi Bougares, Holger Schwenk, Yoshua Bengio (2015). On Using Monolingual Corpora in Neural Machine Translation.||link||Ben Roth|
|Thursday, March 3rd||Stanford Neural Machine Translation Systems for Spoken Language Domain. Minh-Thang Luong and Christopher D. Manning. IWSLT 2015 shared task.||paper slides||Alex Fraser|
Please click here for an NMT reading list, but also see the more general RNN reading list here (scroll down).