Stephen Roller
Ph.D. Alumni
Distributional semantics, multimodal models, bayesian methods.
Homepage:
https://www.cs.utexas.edu/~roller
Publications
Distributional modeling on a diet: One-shot word learning from text only 2017
Su Wang, Stephen Roller, and Katrin Erk, In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), Taipei, Taiwan, November 2017.
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification 2016
Ye Zhang, Stephen Roller, and Byron Wallace., In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), pp. 1522--1527, San Diego, California 2016.
PIC a Different Word: A Simple Model for Lexical Substitution in Context 2016
Stephen Roller and Katrin Erk, In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), pp. 1121-1126, San Diego, California 2016.
Representing Meaning with a Combination of Logical and Distributional Models 2016
I. Beltagy, Stephen Roller, Pengxiang Cheng, Katrin Erk, and Raymond J. Mooney, The special issue of Computational Linguistics on Formal Distributional Semantics, Vol. 42, 4 (2016).
Inclusive yet Selective: Supervised Distributional Hypernymy Detection 2014
Stephen Roller, Katrin Erk, and Gemma Boleda, In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), pp. 1025--1036, Dublin, Ireland, August 2014.
UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Stephen Roller, Gemma Boleda, and Katrin Erk, and Raymond J. Mooney, In The 8th Workshop on Semantic Evaluation (SemEval-2014), pp. 796--801, Dublin, Ireland, August 2014.
A Multimodal LDA Model Integrating Textual, Cognitive and Visual Modalities 2013
Stephen Roller and Sabine Schulte im Walde, In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), pp. 1146--1157, Seattle, WA, October 2013.
Areas of Interest
Combining Logical and Distributional Semantics Deep Learning Language and Vision Lexical Semantics Machine Learning Natural Language Processing Unsupervised Learning, Clustering, and Self-Organization
Labs
Formerly affiliated with Machine Learning