Dani Yogatama
Dani Yogatama
Verifierad e-postadress på google.com - Startsida
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Deep speech 2: End-to-end speech recognition in english and mandarin
D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ...
International conference on machine learning, 173-182, 2016
Grandmaster level in StarCraft II using multi-agent reinforcement learning
O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ...
Nature 575 (7782), 350-354, 2019
Part-of-speech tagging for twitter: Annotation, features, and experiments
K Gimpel, N Schneider, B O'Connor, D Das, D Mills, J Eisenstein, ...
Carnegie-Mellon Univ Pittsburgh Pa School of Computer Science, 2010
AlphaStar: Mastering the Real-Time Strategy Game StarCraft II
O Vinyals, I Babuschkin, J Chung, M Mathieu, M Jaderberg, W Czarnecki, ...
On the cross-lingual transferability of monolingual representations
M Artetxe, S Ruder, D Yogatama
arXiv preprint arXiv:1910.11856, 2019
Generative and discriminative text classification with recurrent neural networks
D Yogatama, C Dyer, W Ling, P Blunsom
arXiv preprint arXiv:1703.01898, 2017
Sparse overcomplete word vector representations
M Faruqui, Y Tsvetkov, D Yogatama, C Dyer, N Smith
ACL 2015, 2015
Learning to compose words into sentences with reinforcement learning
D Yogatama, P Blunsom, C Dyer, E Grefenstette, W Ling
arXiv preprint arXiv:1611.09100, 2016
Efficient Transfer Learning Method for Automatic Hyperparameter Tuning
D Yogatama, G Mann
Proceedings of the 17th International Conference on Artificial Intelligence …, 2014
Embedding methods for fine grained entity type classification
D Yogatama, D Gillick, N Lazic
Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015
Program induction by rationale generation: Learning to solve and explain algebraic word problems
W Ling, D Yogatama, C Dyer, P Blunsom
arXiv preprint arXiv:1705.04146, 2017
Learning and evaluating general linguistic intelligence
D Yogatama, CM d'Autume, J Connor, T Kocisky, M Chrzanowski, L Kong, ...
arXiv preprint arXiv:1901.11373, 2019
LSTMs can learn syntax-sensitive dependencies well, but modeling structure makes them better
A Kuncoro, C Dyer, J Hale, D Yogatama, S Clark, P Blunsom
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
Predicting a scientific community’s response to an article
D Yogatama, M Heilman, B O’Connor, C Dyer, BR Routledge, NA Smith
Proceedings of the 2011 conference on empirical methods in natural language …, 2011
Achieving verified robustness to symbol substitutions via interval bound propagation
PS Huang, R Stanforth, J Welbl, C Dyer, D Yogatama, S Gowal, ...
arXiv preprint arXiv:1909.01492, 2019
Jointly learning sentence embeddings and syntax with unsupervised tree-lstms
J Maillard, S Clark, D Yogatama
Natural Language Engineering 25 (4), 433-449, 2019
Learning Word Representations with Hierarchical Sparse Coding
D Yogatama, M Faruqui, C Dyer, NA Smith
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015
Linguistic Structured Sparsity in Text Categorization
D Yogatama, NA Smith
Proceedings of the 51st Annual Meeting of the Association for Computational …, 2014
Episodic memory in lifelong language learning
CM d'Autume, S Ruder, L Kong, D Yogatama
arXiv preprint arXiv:1906.01076, 2019
A Mutual Information Maximization Perspective of Language Representation Learning
L Kong, CM d'Autume, W Ling, L Yu, Z Dai, D Yogatama
International Conference on Learning Representations, 2020
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Artiklar 1–20