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
Thursdays 14:30 s.t., location is C105 (CIS Besprechungsraum).
Click here for directions to CIS.
If this page appears to be out of date, use the refresh button of your browser
Date | Paper | Links | Discussion Leader |
Thursday, April 28th | Karthik Narasimhan, Tejas Kulkarni, Regina Barzilay (2015). Language Understanding for Text-based Games Using Deep Reinforcement Learning. Proceedings of EMNLP (Best paper honorable mention) | paper and slides | David Kaumanns |
Thursday, May 19th | Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Jozefowicz, Samy Bengio (2016). Generating Sentences from a Continuous Space. arXiv preprint. | paper | Ben Roth |
Thursday, June 9th | Rico Sennrich, Barry Haddow, Alexandra Birch (2015). Neural Machine Translation of Rare Words with Subword Units. arXiv preprint. | paper | Matthias Huck |
Thursday, June 23rd | Junyoung Chung, Kyunghyun Cho, Yoshua Bengio (2016). A Character-level Decoder without Explicit Segmentation for Neural Machine Translation. arXiv preprint. | paper | Ales Tamchyna |
Wednesday, July 13th, at 12:00 | SPECIAL TALK: Prof. Marcello Federico (FBK Trento) - Machine Translation Adaptation from Translation Memories in ModernMT, in room BU 101 | ||
Thursday, July 14th | Carl Doersch (2016). Tutorial on Variational Autoencoders. arXiv preprint. | paper | Yadollah Yaghoobzadeh |
Thursday, July 21st | Yangfeng Ji, Gholamreza Haffari, Jacob Eisenstein (2016). A Latent Variable Recurrent Neural Network for Discourse Relation Language Models. NAACL 2016 | paper | Liane Guillou |
Thursday, July 28th | Presentation by Ivan Bilan on Bilan+Zhekova submission to the PAN shared task | No Reading | |
Thursday, August 18th | 5 favorite papers from ACL 2016, WMT 2016, etc. (Strict 1 minute per paper) | Everyone (Please Bring a Handout) | |
Thursday, August 25th | Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas Mikolov (2016). Enriching Word Vectors with Subword Information. arXiv preprint. | paper | |
Thursday, October 6th | Dan Gillick, Cliff Brunk, Oriol Vinyals, Amarnag Subramanya (2016). Multilingual Language Processing From Bytes. HLT-NAACL 2016. | paper | Hinrich Schütze |
Thursday, October 13th | Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, Hang Li (2016). Modeling Coverage for Neural Machine Translation. ACL 2016 | paper | Tsuyoshi Okita |
Further literature:
Please click here for an NMT reading list, but also see the more general RNN reading list here (scroll down).