Dzmitry Bahdanau


2018

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Commonsense mining as knowledge base completion? A study on the impact of novelty
Stanislaw Jastrzębski | Dzmitry Bahdanau | Seyedarian Hosseini | Michael Noukhovitch | Yoshua Bengio | Jackie Cheung
Proceedings of the Workshop on Generalization in the Age of Deep Learning

Commonsense knowledge bases such as ConceptNet represent knowledge in the form of relational triples. Inspired by recent work by Li et al., we analyse if knowledge base completion models can be used to mine commonsense knowledge from raw text. We propose novelty of predicted triples with respect to the training set as an important factor in interpreting results. We critically analyse the difficulty of mining novel commonsense knowledge, and show that a simple baseline method that outperforms the previous state of the art on predicting more novel triples.

2014

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Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
Jean Pouget-Abadie | Dzmitry Bahdanau | Bart van Merriënboer | Kyunghyun Cho | Yoshua Bengio
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation

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On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
Kyunghyun Cho | Bart van Merriënboer | Dzmitry Bahdanau | Yoshua Bengio
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation

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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
Kyunghyun Cho | Bart van Merriënboer | Caglar Gulcehre | Dzmitry Bahdanau | Fethi Bougares | Holger Schwenk | Yoshua Bengio
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)