Jason Weston


Jason Weston
Research Scientist at Meta AI, USA and Visiting Research Professor at NYU.
Email:

Biography I earned my PhD in machine learning at Royal Holloway, University of London and at AT&T Research in Red Bank, NJ (advisors: Alex Gammerman, Volodya Vovk and Vladimir Vapnik) in 2000. From 2000 to 2001, I was a researcher at Biowulf technologies. From 2002 to 2003 I was a research scientist at the Max Planck Institute for Biological Cybernetics, Tuebingen, Germany. From 2003 to 2009 I was a research staff member at NEC Labs America, Princeton. From 2009 to 2014 I was a research scientist at Google, NY. [see full bio]

Publications

  • S Saha, Omer Levy, A Celikyilmaz, M Bansal, J Weston, X Li Branch-Solve-Merge Improves Large Language Model Evaluation and Generation. arXiv:2310.15123
  • H Chen, R Pasunuru, J Weston, A Celikyilmaz Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading. arXiv:2310.05029
  • S Dhuliawala, M Komeili, J Xu, R Raileanu, X Li, A Celikyilmaz, J Weston Chain-of-Verification Reduces Hallucination in Large Language Models. arXiv:2309.11495
  • X Li, P Yu, C Zhou, T Schick, L Zettlemoyer, O Levy, J Weston, M Lewis Self-Alignment with Instruction Backtranslation. arXiv:2308.06259
  • R Yuanzhe Pang, S Roller, K Cho, H He, J Weston Leveraging Implicit Feedback from Deployment Data in Dialogue. arXiv:2307.14117
  • W Yuan, K Cho, J Weston System-Level Natural Language Feedback. arXiv:2306.13588
  • J. Xu, D. Ju, J. Lane, M. Komeili, E. M. Smith, M. Ung, M. Behrooz, W. Ngan, R. Moritz, S. Sukhbaatar, Y-L.Boureau, J. Weston, K. Shuster. Improving Open Language Models by Learning from Organic Interactions. arXiv:2306.04707 [project]
  • M. Behrooz, W. Ngan, J. Lane, G. Morse, B. Babcock, K. Shuster, M. Komeili, M. Chen, M. Kambadur, Y-L. Boureau, J. Weston. The HCI Aspects of Public Deployment of Research Chatbots: A User Study, Design Recommendations, and Open Challenges. arXiv:2306.04765
  • I Schlag, S Sukhbaatar, A Celikyilmaz, W Yih, J Weston, J Schmidhuber, Xian Li. Large language model programs. arXiv:2305.05364
  • J Lanchantin, S Toshniwal, J Weston, A Szlam, S Sukhbaatar. Learning to Reason and Memorize with Self-Notes. arXiv:2305.00833
  • J Wei, K Shuster, A Szlam, J Weston, J Urbanek, M Komeili. Multi-party chat: Conversational agents in group settings with humans and models. arXiv:2304.13835
  • K Arora, TJ O'Donnell, D Precup, J Weston, JCK Cheung. The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation. arXiv:2302.06784
  • A Gurung, M Komeili, A Szlam, J Weston, J Urbanek. Infusing Commonsense World Models with Graph Knowledge. arXiv:2301.05746
  • L Adolphs, T Gao, J Xu, K Shuster, S Sukhbaatar, J Weston. The CRINGE Loss: Learning what language not to model. arXiv:2211.05826 [project]
  • W Shi, E Dinan, K Shuster, J Weston, J Xu. When Life Gives You Lemons, Make Cherryade: Converting Feedback from Bad Responses into Good Labels. arXiv:2210.15893 [project]
  • D Ju, J Xu, YL Boureau, J Weston. Learning from data in the mixed adversarial non-adversarial case: Finding the helpers and ignoring the trolls. arXiv:2208.03295 [project]
  • J Xu, M Ung, M Komeili, K Arora, YL Boureau, J Weston. Learning New Skills after Deployment: Improving open-domain internet-driven dialogue with human feedback. arXiv:2208.03270 [project]
  • Kurt Shuster, Jing Xu, Mojtaba Komeili, Da Ju, Eric Michael Smith, Stephen Roller, Megan Ung, Moya Chen, Kushal Arora, Joshua Lane, Morteza Behrooz, William Ngan, Spencer Poff, Naman Goyal, Arthur Szlam, Y-Lan Boureau, Melanie Kambadur, Jason Weston. BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage. arXiv:2208.03188 [project]
  • K Arora, K Shuster, S Sukhbaatar, J Weston. DIRECTOR: Generator-Classifiers For Supervised Language Modeling. arXiv:2206.07694 [project]
  • K Shuster, M Komeili, L Adolphs, S Roller, A Szlam, J Weston. Language models that seek for knowledge: Modular search & generation for dialogue and prompt completion. arXiv:2203.13224 [project]
  • EM Smith, O Hsu, R Qian, S Roller, YL Boureau, J Weston. Human Evaluation of Conversations is an Open Problem: comparing the sensitivity of various methods for evaluating dialogue agents. arXiv:2201.04723 [project]
  • K Shuster, J Urbanek, A Szlam, J Weston. Am i me or you? state-of-the-art dialogue models cannot maintain an identity. arXiv:2112.05843 [project]
  • Leonard Adolphs, Kurt Shuster, Jack Urbanek, Arthur Szlam, Jason Weston. Reason first, then respond: Modular Generation for Knowledge-infused Dialogue. arXiv:2111.05204 [project]
  • Sam Shleifer, Jason Weston, Myle Ott. NormFormer: Improved Transformer Pretraining with Extra Normalization. arXiv:2110.09456 [project]
  • Mojtaba Komeili, Kurt Shuster, Jason Weston Internet-Augmented Dialogue Generation. arXiv:2107.07566 [project]
  • Jing Xu, Arthur Szlam, Jason Weston. Beyond Goldfish Memory: Long-Term Open-Domain Conversation. arXiv:2107.07567 [project]
  • S. Roller, S. Sukhbaatar, A. Szlam, J. Weston. Hash Layers For Large Sparse Models. arXiv:2106.04426 [project]
  • D. Ju, S. Roller, S. Sukhbaatar, J. Weston. Staircase Attention for Recurrent Processing of Sequences. arXiv:2106.04279 [project]
  • P. Ammanabrolu, J. Urbanek, M. Li, A. Szlam, T. Rocktäschel, J. Weston. How to Motivate Your Dragon: Teaching Goal-Driven Agents to Speak and Act in Fantasy Worlds. arXiv:2010.00685 and NAACL 2021 [project]
  • J. Xu, D. JU, M. Li, Y.-L. Boureau, J. Weston and E. Dinan. Bot-Adversarial Dialogue for Safe Conversational Agents. NAACL 2021 [project]
  • K. Shuster, E. Michael Smith, D. Ju, J. Weston Multi-Modal Open-Domain Dialogue. arXiv:2010.01082 [project]
  • J. Xu, D. JU, M. Li, Y.-L. Boureau, J. Weston and E. Dinan Recipes for Safety in Open-domain Chatbots. arXiv:2010.01082 [project]
  • S. Sukhbaatar, D. JU, S. Poff, S. Roller, A. Szlam, J. Weston, A. Fan Not All Memories are Created Equal: Learning to Expire.
  • E. Dinan, A. Fan, L. Wu, J. Weston, D. Kiela, A. Williams Multi-Dimensional Gender Bias Classification. arXiv:2005.00614 and EMNLP 2020
  • K Shuster, S Poff, M Chen, D Kiela, J Weston Retrieval Augmentation Reduces Hallucination in Conversation. arXiv:2104.07567
  • Y. Nie, M. Williamson, M. Bansal, D. Kiela, J. Weston I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling. arXiv:2012.13391 [project]
  • K. Shuster, J. Urbanek, E. Dinan, A. Szlam, J. Weston Deploying Lifelong Open-Domain Dialogue Learning. arXiv:2008.08076 [project]
  • S. Roller, E. Dinan, N. Goyal, D. Ju, M. Williamson, Y. Liu, J. Xu, M. Ott, K. Shuster, E. M. Smith, Y-L. Boureau, J Weston. Recipes for building an open-domain chatbot. arXiv:2004.13637 and EACL 2020 [project]
  • Stephen Roller*, Y-Lan Boureau*, Jason Weston*, Antoine Bordes, Emily Dinan, Angela Fan, David Gunning, Da Ju, Margaret Li, Spencer Poff, Pratik Ringshia, Kurt Shuster, Eric Michael Smith, Arthur Szlam, Jack Urbanek, Mary Williamson. Open-domain conversational agents: current progress, open problems, and future directions.. arXiv:2006.12442
  • Eric Smith, Mary Williamson, Kurt Shuster, Jason Weston, Y-Lan Boureau. Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills. ACL'20 & arXiv:2004.08449 [project]
  • S. Prabhumoye, M. Li, J. Urbanek, E. Dinan, D. Kiela, J. Weston, A. Szlam I love your chain mail! Making knights smile in a fantasy game world: Open-domain goal-oriented dialogue agents. arXiv:2002.02878 [project]
  • D. Ju, K. Shuster, Y-L. Boureau, J. Weston All-in-One Image-Grounded Conversational Agents. arXiv:1912.12394
  • Xinyi Wang, Jason Weston, Michael Auli, Yacine Jernite. Improving Conditioning in Context-Aware Sequence to Sequence Models. arXiv:1911.09728
  • Angela Fan, Jack Urbanek, Pratik Ringshia, Emily Dinan, Emma Qian, Siddharth Karamcheti, Shrimai Prabhumoye, Douwe Kiela, Tim Rocktaschel, Arthur Szlam, Jason Weston. Generating Interactive Worlds with Text. arXiv:1911.09194 [project]
  • Margaret Li, Stephen Roller, Ilia Kulikov, Sean Welleck, Y-Lan Boureau, Kyunghyun Cho, Jason Weston. Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training. ACL'20 & arXiv:1911.03860
  • Emily Dinan, Angela Fan, Adina Williams, Jack Urbanek, Douwe Kiela, Jason Weston. Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation. arXiv:1911.03842 [project]
  • Kurt Shuster, Da Ju, Stephen Roller, Emily Dinan, Y-Lan Boureau, Jason Weston. The Dialogue Dodecathlon: Open-Domain Knowledge and Image Grounded Conversational Agents. ACL'20 & arXiv:1911.03768 [project]
  • Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, Douwe Kiela. Adversarial NLI: A New Benchmark for Natural Language Understanding. ACL'20 & arXiv:1910.14599 [project]
  • K. Shuster, S. Humeau, A.Bordes, J. Weston. Image Chat: Engaging Grounded Conversations. ACL'20 & arXiv:1811.00945.
  • S. Humeau, K. Shuster, M.-A. Lachaux, J. Weston. Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring. ICLR'20 & arXiv:1903.03094.
  • M. Li, J. Weston, S. Roller. ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisons. arXiv:1909.03087.
  • A. Szlam, J. Gray, K. Srinet, Y. Jernite, A. Joulin, G. Synnaeve, D. Kiela, H. Yu, Z. Chen, S. Goyal, D. Guo, D. Rothermel, C. L. Zitnick, J. Weston. Why Build an Assistant in Minecraft? arXiv:1907.09273.
  • S. Welleck, I. Kulikov, S. Roller, E. Dinan, K. Cho, J. Weston. Neural Text Generation with Unlikelihood Training. EMNLP '19 & arXiv:1909.05863. [code]
  • E. Dinan, V. Logacheva, V. Malykh, A. Miller, K. Shuster, J. Urbanek, D. Kiela, A. Szlam, I. Serban, R. Lowe, S. Prabhumoye, A. Black, A. Rudnicky, J. Williams, J. Pineau, M. Burtsev, J. Weston. The Second Conversational Intelligence Challenge (ConvAI2). arXiv:1902.00098.
  • D. Kang, A. Balakrishnan, P. Shah, P. Crook, Y-L. Boureau, J. Weston. Recommendation as a Communication Game: Self-Supervised Bot-Play for Goal-oriented Dialogue EMNLP '19 & arXiv:1909.03922.
  • E. Perez, S. Karamcheti, R. Fergus, J. Weston, D. Kiela, K. Cho Finding Generalizable Evidence by Learning to Convince Q&A Models. EMNLP '19 & arXiv:1909.05863.
  • E. Dinan, S. Humeau, B. Chintagunta, J. Weston. Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack. EMNLP '19 & arXiv:1908.06083.
  • J. Urbanek, A. Fan, S. Karamcheti, S. Jain, S. Humeau, E. Dinan, T. Rocktäschel, D. Kiela, A. Szlam, J. Weston. Learning to Speak and Act in a Fantasy Text Adventure Game. EMNLP '19 & arXiv:1903.03094.
  • A. Fan, Y. Jernite, E. Perez, D. Grangier, J. Weston, M. Auli. ELI5: Long Form Question Answering. ACL '19 & https://arxiv.org/abs/1907.09190.
  • B. Hancock, A. Bordes, PE. Mazare, J. Weston. Learning from Dialogue after Deployment: Feed Yourself, Chatbot! ACL 2019 and arXiv:1901.05415.
  • S. Welleck, J. Weston, A. Szlam, K. Cho. Dialogue Natural Language Inference. ACL 2019 and arXiv:1811.00671.
  • A. See, S. Roller, D. Kiela and J. Weston. What makes a good conversation? How controllable attributes affect human judgments NAACL 2019.
  • K. Shuster, S. Humeau, H. Hu, A.Bordes, J. Weston. Engaging Image Captioning Via Personality. CVPR 2019 and arXiv:1810.10665.
  • I. Kulikov, A. H. Miller, K. Cho, J. Weston. Importance of a Search Strategy in Neural Dialogue Modelling. arXiv:1811.00907.
  • E. Dinan, S. Roller, K. Shuster, A. Fan, M. Auli, J. Weston. Wizard of Wikipedia. ICLR '19. [data]
  • D. Weissenborn, D. Kiela, J. Weston, K. Cho. Contextualized Role Interaction for Neural Machine Translation.
  • J. Bastings, M. Baroni, J. Weston, K. Cho, D. Kiela. Jump to better conclusions: SCAN both left and right. Workshop on Analyzing and Interpreting Neural Networks for NLP, EMNLP. Brussels, Belgium. [code]
  • J. Weston, E. Dinan, A. H. Miller. Retrieve and Refine: Improved Sequence Generation Models For Dialogue. arXiv:1808.04776.
  • H. de Vries, K. Shuster, D. Batra, D. Parikh, J. Weston, D. Kiela. Talk the Walk: Navigating New York City through Grounded Dialogue. arXiv:1807.03367. Visual Learning and Embodied Agents in Simulation Environments, ECCV 2018 Workshop.
  • C. Resnick, I. Kulikov, K. Cho, J. Weston. Vehicle Communication Strategies for Simulated Highway Driving. arXiv:1804.07178.
  • S Zhang, E. Dinan, J. Urbanek, A. Szlam, D. Kiela, J. Weston. Personalizing Dialogue Agents: I have a dog, do you have pets too? ACL 2018. arXiv:1801.07243. [project]
  • Z. Yang, S. Zhang, J. Urbanek, W. Feng, A. H. Miller, A. Szlam, D. Kiela, J. Weston. Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent. ICLR 2018. arXiv:1711.07950. [project]
  • J. Lee, K. Cho, J. Weston, D. Kiela. Emergent Translation in Multi-Agent Communication. ICLR 2018. arXiv:1710.06922.
  • L. Wu, A. Fisch, S. Chopra, K. Adams, A. Bordes, J. Weston. StarSpace: Embed All The Things! AAAI, 2017. [project]
  • A. H. Miller, W. Feng, A. Fisch, J. Lu, D. Batra, A. Bordes, D. Parikh, J. Weston. ParlAI: A Dialog Research Software Platform. [project]
  • D. Chen, A. Fisch, J. Weston, A. Bordes. Reading Wikipedia to Answer Open-Domain Questions. ACL 2017. arXiv:1704.00051.
  • M. Henaff, J. Weston, A. Szlam, A. Bordes, Y. LeCun. Tracking the World State with Recurrent Entity Networks. ICLR 2017. arXiv:1612.03969.
  • J. Li, A. H. Miller, S. Chopra, M. Ranzato, J. Weston. Dialogue Learning With Human-in-the-Loop. ICLR 2017. arXiv:1611.09823. [code+data]
  • J. Li, A. H. Miller, S. Chopra, M. Ranzato, J. Weston. Learning through Dialogue Interactions by Asking Questions. ICLR 2017. [code+data]
  • A. Bordes, Y-Lan Boureau, J. Weston Learning End-to-End Goal-Oriented Dialog. ICLR 2017. arXiv:1605.07683. [data]
  • A. H. Miller, A. Fisch, J. Dodge, A. Karimi, A. Bordes, J. Weston. Key-Value Memory Networks for Directly Reading Documents. EMNLP 2016. arXiv:1606.03126. [code][data]
  • J. Weston. Dialog-based Language Learning. NIPS 2016. arXiv:1604.06045. [code] [data]
  • F. Hill, A. Bordes, S. Chopra, J. Weston. The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations. ICLR 2016. arXiv:1511.02301. [data]
  • J. Dodge, A. Gane, X. Zhang, A. Bordes, S. Chopra, A. Miller, A. Szlam, J. Weston. Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems. ICLR 2016. arXiv:1511.06931. [data]
  • A. M. Rush, S. Chopra and J. Weston. A Neural Attention Model for Abstractive Sentence Summarization. EMNLP 2015 (and arXiv:1509.00685). [code]
  • S. Sukhbaatar, A. Szlam, J. Weston, R. Fergus. End-To-End Memory Networks. NIPS 2015 (and arXiv:1503.08895). [code]
  • A. Bordes, N. Usunier, S. Chopra, J. Weston. Large-scale Simple Question Answering with Memory Networks. arXiv:1506.02075. [data]
  • E. Denton, J.Weston, M. Paluri, L. Bourdev, R. Fergus. User Conditional Hashtag Prediction for Images. KDD 2015.
  • S. Wiseman, A. M. Rush, S. Shieber, J. Weston. Learning Anaphoricity and Antecdent Ranking Features for Coreference Resolution. ACL 2015.
  • J. Weston, A. Bordes, S. Chopra, A. M. Rush, B. van Merriënboer, A. Joulin, T. Mikolov. Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks. ICLR 2016. arXiv:1502.05698. [data & code]
  • J. Weston, S. Chopra, A. Bordes. Memory Networks. ICLR 2015 (and arXiv:1410.3916).
  • A. Bordes, S. Chopra, J. Weston. Question Answering with Subgraph Embeddings. EMNLP 2014 (and arXiv:1406.3676).
  • J. Weston, S. Chopra, K. Adams. #TagSpace: Semantic Embeddings from Hashtags. EMNLP 2014.
  • A. Bordes, J. Weston, N. Usunier. Open Question Answering with Weakly Supervised Embedding Models. ECML 2014 (and arXiv:1404.4326).
  • J. Weston, R. Weiss, H. Yee. Affinity Weighted Embedding. ICML 2014.
  • K. M. Hermann, D. Das, J. Weston and K. Ganchev, Semantic Frame Identification with Distributed Word Representations. ACL 2014.
  • M. R. Gupta, S. Bengio and J. Weston, Training Highly Multiclass Classi fiers. JMLR 2014.
  • Y. Qi, S. Das, R. Collobert, and J. Weston. Deep Learning for Character-based Information Extraction. ECIR 2014.
  • A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston and O. Yakhnenko, Translating Embeddings for Modeling Multi-relational Data. NIPS 2013.
  • J. Weston, H. Yee, R. Weiss, Learning to Rank Recommendations with the k-Order Statistic Loss. RecSys 2013.
  • J. Weston, R, Weiss, H. Yee, Nonlinear Latent Factorization by Embedding Multiple User Interests. RecSys 2013.
  • J. Weston, A. Bordes, O. Yakhnenko, N. Usunier. Connecting Language and Knowledge Bases with Embedding Models for Relation Extraction. EMNLP, 2013.
  • A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, O. Yakhnenko. Irreflexive and Hierarchical Relations as Translations. Structured Learning on Graphs workshop, ICML 2013.
  • A. Bordes, X. Glorot J. Weston, Y. Bengio. A Semantic Matching Energy Function for Learning with Multi-relational Data. To Appear in the Special Issue on Learning Semantics in Machine Learning Journal.
  • G. Mesnil, A. Bordes, J. Weston, G. Chechik, and Y. Bengio. Learning Semantic Representations Of Objects And Their Parts. To Appear in the Special Issue on Learning Semantics in Machine Learning Journal.
  • J. Weston, R. Weiss, H. Yee. Affinity Weighted Embedding, ICLR 2013 .
  • X. Glorot, A. Bordes, J. Weston, Y. Bengio A Semantic Matching Energy Function for Learning with Multi-relational Data, ICLR 2013 .
  • J. Weston, A. Makadia, H. Yee. Label Partitioning for Sublinear Ranking, ICML 2013 .
  • J. Weston, F. Ratle, H. Mobahi, R. Collobert. Deep Learning via Semi-Supervised Embedding. Chapter of Neural Networks Tricks of the Trade, Reloaded, Springer LNCS.
  • J. Weston and J. Blitzer. Latent Structured Ranking. UAI 2012.
  • A. Lucchi and J. Weston. Joint Image and Word Sense Discrimination For Image Retrieval. ECCV 2012.
  • J. Weston, C. Wang, R. Weiss and A. Berenzweig. Latent Collaborative Retrieval. ICML 2012.
  • A. Senior, Y. Cho and J. Weston. Learning improved linear transforms for speech recognition. ICASSP 2012.
  • A. Bordes, X. Glorot, J. Weston and Y. Bengio. Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing. AISTATS 2012.
  • M. Spivak, D. Tomazela, J. Weston, M. MacCoss, W. Stafford Noble. Direct maximization of protein identifications from tandem mass spectra. Molecular & Cellular Proteomics.
  • Y. Qi, M. Oja, J. Weston and W. S. Noble. A unified multitask architecture for predicting local protein properties. PLoS ONE.
  • J. Weston, S. Bengio, P. Hamel. Large-Scale Music Annotation and Retrieval: Learning to Rank in Joint Semantic Spaces. Journal of New Music Research.
  • A. Bordes, J. Weston, R. Collobert and Y. Bengio. Learning Structured Embeddings of Knowledge Bases. AAAI 2011. *ERRATUM*
  • I. Melvin, J. Weston, C. Leslie, W. S. Noble. Detecting remote evolutionary relationships among proteins by large-scale semantic embedding. PLoS Computational Biology, 2011.
  • R. Collobert, J. Weston, L. Bottou, M. Karlen, K. Kavukcuoglu, P. Kuksa. Natural Language Processing (almost) from Scratch . JMLR Volume 12, 2011 (To Appear).
  • J. Weston, S. Bengio, N. Usunier. Wsabie: Scaling Up To Large Vocabulary Image Annotation. IJCAI, 2011.
  • S. Bengio, J. Weston, D. Grangier. Label Embedding Trees for Large Multi-Class Tasks. NIPS 2010.
  • P. Kuksa, Y. Qi, B. Bai, R. Collobert, J. Weston. Semi-Supervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction. ECML 2010.
  • J. Weston, S. Bengio, N. Usunier. Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings. ECML PKDD 2010 special issue of the Machine Learning journal.
  • J. Weston, S. Bengio, N. Usunier. Large Scale Image Annotation: Learning to Rank with Joint Word-Image Embeddings. ECML, 2010.
  • Y. Qi, O. Tastan, J. Carbonell, J. Klein-Seetharaman, J. Weston. Semi-Supervised Multi-Task Learning for Predicting Interactions between HIV-1 and Human Proteins. European Conference on Computational Biology (ECCB), 2010.
  • N. Usunier, A. Bordes, J. Weston. Label Ranking under Ambiguous Supervision: An Application for Learning Semantic Correspondences. ICML, 2010.
  • B. Bai, J. Weston, D. Grangier, R. Collobert, C. Cortes, M. Mohri. Half Transductive Ranking. AISTATS, 2010.
  • A. Bordes, N. Usunier, R. Collobert, J. Weston. Towards Understanding Situated Natural Language. AISTATS, 2010.
  • B. Bai, J. Weston, D. Grangier, R. Collobert, C. Cortes, M. Mohri. Half Transductive Ranking. NIPS workshop : Advances in Ranking, 2009.
  • A. Bordes, N. Usunier, J. Weston and R. Collobert. Learning to Disambiguate Natural Language Using World Knowledge NIPS workshop: Grammar Induction, Representation of Language and Language Learning, 2009.
  • B. Bai, J. Weston, D. Grangier, R. Collobert, K. Sadamasa, Y. Qi, C. Cortes, M. Mohri. Polynomial Semantic Indexing. NIPS, 2009.
  • F. Ratle, G. Camps-Valls, J. Weston. Semi-Supervised Neural Networks for Efficient Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing.
  • Y. Qi, P. Kuksa, R. Collobert, K. Sadamasa, K. Kavukcuoglu and J. Weston. Semi-Supervised Sequence Labeling with Self-Learned Features. IEEE International Conference on Data Mining (ICDM), 2009.
  • B. Bai, J. Weston, D. Grangier, R. Collobert, K. Sadamasa, Y. Qi, O. Chapelle, K. Weinberger. Learning to Rank with (a Lot of) Word Features. Special Issue on Learning to Rank for Information Retrieval, Journal of Information Retrieval.
  • T. Barnickel, J. Weston, R. Collobert, H-W. Mewes, V. Stuempflen. Large Scale Application of Neural Network Based Semantic Role Labeling for Automated Relation Extraction from Biomedical Texts. PLoS ONE.
  • Y. Qi, R. Collobert, P. Kuksa, K. Kavukcuoglu and J. Weston. Combining Labeled and Unlabeled Data with Word-Class Distribution Learning. The 18th ACM Conference on Information and Knowledge Management (CIKM), 2009.
  • B. Bai, J. Weston, D. Grangier, R. Collobert, O. Chapelle, K. Weinberger. Supervised Semantic Indexing. The 18th ACM Conference on Information and Knowledge Management (CIKM), 2009.
  • B. Bai, J. Weston, D. Grangier, R. Collobert, Y. Qi, K. Sadamasa, O. Chapelle, K. Weinberger. Learning to Rank with Low Rank. Workshop on Learning to Rank For Information Retrieval, SIGIR 2009.
  • M. Spivak, J. Weston, L. Bottou, L. Kall, W. Stafford Noble. Improvements to the Percolator algorithm for peptide identification from shotgun proteomics data sets. Journal of Proteome Research.
  • Y. Bengio, J. Louradour, R. Collobert, J. Weston. Curriculum Learning. ICML 2009. *ERRATUM*
  • H. Mobahi, R. Collobert, J. Weston. Deep Learning from Temporal Coherence in Video. ICML 2009.
  • B. Bai, J. Weston, R. Collobert, D. Grangier. Supervised Semantic Indexing. Poster paper, ECIR 2009.
  • I. Melvin, J. Weston, C. Leslie, W. S. Noble. RANKPROP: a web server for protein remote homology detection . Bioinformatics.
  • I. Melvin, J. Weston, C. Leslie, W. S. Noble. Combining classifiers for improved classification of proteins from sequence or structure. BMC Bioinformatics.
  • F. Ratle, J. Weston, M. L. Miller. "Large-scale clustering through functional embedding", European Conference on Machine Learning (ECML 2008).
  • R. Collobert, J. Weston. "A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning", ICML 2008.
  • J. Weston, F. Ratle, R. Collobert. "Deep Learning via Semi-Supervised Embedding" ICML 2008.
  • M. Karlen, J. Weston, A. Erkan, R. Collobert. "Large Scale Manifold Transduction", ICML 2008.
  • J. Weston. "Large Scale Semi-Supervised Learning". Proceedings of NATO Advanced Study Institute on Mining Massive Data Sets for Security, IOS Press.
  • S. Sonnenburg, M. L. Braun, C. Soon Ong, S. Bengio, L. Bottou, G. Holmes, Y. LeCun, K. Mueller, F. Pereira, C. Edward Rasmussen, G. Raetsch, B. Schoelkopf, A. Smola, P. Vincent, J. Weston, R. Williamson. "The Need for Open Source Software in Machine Learning", JMLR 8(Oct):2443--2466, 2007.
  • R. Collobert, F. Sinz, J. Weston, L. Bottou. "Trading Convexity for Scalability." Large-Scale Kernel Machines, pp. 275-299, Cambridge, MA, MIT Press.
  • L. Kall, J. Canterbury, J. Weston, W. S. Noble, M. J. MacCoss. Semi-Supervised Learning for Peptide Identification from Shotgun Proteomics Datasets". Nature Methods (2007).
  • Large Scale Kernel Machines, Edited by Leon Bottou, Olivier Chapelle, Dennis DeCoste, and Jason Weston, Neural Information Processing Series, MIT Press, Cambridge, MA., 2007.
  • R. Collobert, J. Weston. Fast Semantic Extraction Using a Novel Neural Network Architecture. 45th Annual Meeting of the Association for Computational Linguistics, 2007.
  • I. Melvin, Ie, Eugene and Weston, Jason and Noble, William Stafford and Leslie, Christina: Multi-class protein classification using adaptive codes. Journal of Machine Learning Research, 2007.
  • A. Bordes, L. Bottou, P. Gallinari, J. Weston Solving MultiClass Support Vector Machines with LaRank. . ICML 2007.
  • I. Melvin, E. Ie, R. Kuang, J. Weston, W. Noble, C. Leslie SVM-fold : a tool for discriminative multi-class protein fold and superfamily recognition. . BMC Bioinformatics, 2007.
  • C. Cortes, M. Mohri, J. Weston. A General Regression Framework for Learning String-to-String Mappings . In Predicting Structured Data. The MIT Press, 2007.
  • J. Weston, G. BakIr, O. Bousquet, B. Schoelkopf, T. Mann and W. S. Noble. Joint Kernel Maps . In Predicting Structured Data. The MIT Press, 2007.
  • G. BakIr, B. Schoelkopf and J. Weston. On the Pre-Image Problem in Kernel Methods . Kernel Methods in Bioengineering, Signal and Image Processing, 284-302, IDEA GROUP PUBLISHING, Hershey, PA, USA, 2007.
  • R. Collobert, F. Sinz, J. Weston and L. Bottou. Large Scale Transductive SVMs . JMLR, 2006.
  • J. Weston, R. Collobert, F. Sinz, L. Bottou and V. Vapnik. "Inference with the Universum", ICML 2006.
  • R. Collobert, F. Sinz, J. Weston and L. Bottou. "Trading Convexity for Scalability", ICML 2006 - Best paper award.
  • Antoine Bordes, Seyda Ertekin, Jason Weston and Leon Bottou. "Fast Kernel Classifiers with Online and Active Learning". JMLR, 6(Sep):1579--1619, 2005. **SUPPLEMENT - INCLUDING SOFTWARE**
  • William Stafford Noble, Rui Kuang, Christina Leslie and Jason Weston. "Identifying remote protein homologs by network propagation". FEBS Journal, Volume 272 Issue 20 Page 5119, October, 2005.
  • Jason Weston, Rui Kuang, Christina Leslie and William Stafford Noble. "Protein Ranking by Semi-Supervised Network Propagation". BMC Bioinformatics Special Issue.
  • Jason Weston, Christina Leslie, Eugene Ie, Dengyong Zhou, Andre Elisseeff and William Stafford Noble. "Semi-Supervised Protein Classification using Cluster Kernels". Book Chapter for "Semi-Supervised Learning", MIT Press (Editors: O. Chapelle, B. Schoelkopf and A. Zien).
  • Rui Kuang, Jason Weston, William Stafford Noble and Christina Leslie, "Motif-based Protein Ranking by Network Propagation". Bioinformatics, 2005
  • Eugene Ie, Jason Weston, William Stafford Noble and Christina Leslie. "Multi-class protein fold recognition using adaptive codes". ICML, 2005.
  • Corinna Cortes, Mehryar Mohri and Jason Weston. "A General Regression Technique for Learning Transductions". ICML, 2005.
  • Weston, J., B. Schoelkopf and O. Bousquet. "Joint Kernel Maps", Proceedings of the 8th International Work-Conference on Artificial Neural Networks, LNCS 3512, 176-191. (Eds.) Cabestany, J., A. Prieto and F. Sandoval, Springer-Verlag, Heidelberg, Germany, 2005.
  • Jason Weston, Christina Leslie, Eugene Ie, Dengyong Zhou, Andre Elisseeff and William Stafford Noble. "Semi-Supervised Protein Classification using Cluster Kernels". Bioinformatics, 2005.
  • T.N. Lal, O. Chapelle, J. Weston and A. Elisseeff. "Embedded Methods." Chapter in "Feature extraction, foundations and Applications", Editors: Isabelle Guyon, Steve Gunn, Masoud Nikravesh, and Lofti Zadeh. Book in preparation.
  • J. Weston, A. Bordes and L. Bottou. "Online (and Offline) On an Even Tighter Budget", AISTATS 2005. *ERRATUM*
  • G. BakIr, L. Bottou and J. Weston. "Breaking SVM Complexity with Cross-Training", NIPS, 2004.
  • J. Weston, G. BakIr. "Fast Binary and Multi-Output Reduced Set Selection", MPI Technical Report, TR-132, 2004.
  • J. Weston, B. Schoelkopf, O. Bousquet, T. Mann and W. Stafford Noble, "Joint Kernel Maps", MPI Technical Report, TR-131, 2004.
  • J. Weston, A. Eliseeff, D. Zhou, C. Leslie and W. Stafford Noble. Protein ranking: from local to global structure in the protein similarity network. Proceedings of the National Academy of Science. 101(17):6559-6563, 2004.
  • T.N. Lal, M. Schroeder, T. Hinterberger, J. Weston, M. Bogdan, N. Birbaumer and B. Schoelkopf. Support Vector Channel Selection in BCI. IEEE Transactions on Biomedical Engineering 2004.
  • D. Zhou, J. Weston, A. Gretton, O. Bousquet and B. Schoelkopf. Ranking on Data Manifolds. NIPS, 2003.
  • D. Zhou, O. Bousquet, T.N. Lal, J. Weston and B. Schoelkopf. Learning with Local and Global Consistency. NIPS, 2003.
  • J. Weston, C. Leslie, D. Zhou, A. Elisseeff and W. Stafford Noble. Semi-Supervised Protein Classification using Cluster Kernels. NIPS, 2003
  • G. Bakir, J. Weston and B. Schoelkopf. "Learning to find Pre-Images" , NIPS, 2003.
  • J. Eichhorn, A.S. Tolias, A. Zien, M. Kuss, C. E. Rasmussen, J. Weston, N.K. Logothetis and B. Schoelkopf, Prediction on Spike Data Using Kernel Algorithms , NIPS 2003.
  • J. Weston, A. Gretton and A. Elisseeff. SVM Practical Session (How to get good results without cheating) . Machine Learning Summer School 2003, Tuebingen.
  • C. Leslie, E. Eskin, A. Cohen, J. Weston and W. Stafford Noble. "Mismatch String Kernels for Discriminative Protein Classification ". Bioinformatics.
  • F. Perez-Cruz, J. Weston, D. Hermann and B. Schoelkopf. "Extension of the nu-SVM range for Classification", Advances in Learning Theory, IOS Press: NATO-ASI Series in Computer and Systems Sciences, 2003.
  • J. Weston, O. Chapelle, A. Elisseeff, B. Schoelkopf and V. Vapnik. "Kernel Dependency Estimation", NIPS 2002.
  • C. Leslie, E. Eskin, J. Weston and W. Stafford Noble. "Mismatch String Kernels for SVM Protein Classification". NIPS, 2002.
  • D. LaLoudouana and M. Bonouliqui Tarare "Data Set Selection". (slides , video in .rm or .wmv). NIPS, 2002.
  • O. Chapelle, B. Schoelkopf and J. Weston. "Semi-Supervised Learning through Principal Directions Estimation".
  • O. Chapelle, J. Weston and B. Schoelkopf. "Cluster Kernels for Semi-Supervised Learning", NIPS 2002.
  • B. Schoelkopf, J.Weston, E. Eskin, C. Leslie and W. S. Noble. Dealing with Large Diagonals in Kernel Matrices. (or 'A kernel approach for learning from almost orthogonal patterns'). Annals of the Institute of Statistical Mathematics (or ECML'2002 and PKDD'2002).
  • J. Weston, F. Perez-Cruz, O. Bousquet, O. Chapelle, A. Elisseeff and B. Schoelkopf. "Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design". Bioinformatics.
  • A. Elisseeff and J. Weston. "A kernel method for multi-labelled classification" NIPS 14, 2001. (Or see the Tech report).
  • J. Weston, A. Elisseeff, M. Tipping and B. Schoelkopf. "Use of the zero norm with linear models and kernel methods" JMLR special Issue on Variable and Feature selection, 2002.
  • P. Pavlidis , J. Weston, J. Cai and W. Stafford Noble. "Learning gene functional classifications from multiple data types." Journal of Computational Biology.
  • P. Pavlidis, J. Weston, J. Cai and W. Grundy. "Gene functional classification from heterogeneous data" RECOMB'2000.
  • I. Guyon, J. Weston, S. Barnhill and V. Vapnik. "Gene Selection for Cancer Classification using Support Vector Machines." Machine Learning.
  • *ERRATUM*

  • J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio, and V. Vapnik Feature Selection for SVMs . NIPS 13, 2000
  • O. Chapelle, J. Weston, L. Bottou, and V. Vapnik. Vicinal Risk Minimization . NIPS 13, 2000
  • O. Chapelle, V. Vapnik and J. Weston.Transductive Inference for Estimating Values of Functions NIPS 12, 1999.
  • J. Weston, "Extensions to the Support Vector Method", PhD thesis, Royal Holloway University of London, 1999.
  • S. Mika, G. Raetsch, J. Weston, B. Schoelkopf, A. Smola and K.-R. Mueller, "Constructing Descriptive and Discriminative Non-Linear Features: Rayleigh Coefficients in Kernel Feature Spaces". PAMI 2002.
  • S. Mika, G. Raetsch, B. Schoelkopf, A. Smola, J. Weston, and K.-R. Mueller. "Invariant feature extraction and classification in kernel spaces". NIPS 12, 1999.
  • S. Mika, G. Raetsch, J. Weston, B. Schoelkopf, and K.-R. Mueller, "Fisher Discriminant Analysis with Kernels". NNSP'99.
  • R. Herbrich and J. Weston, "Adaptive Margin Support Vector Machines for Classification". ICANN'99. (Or see a longer version in "Advances in Large Margin Classifiers", MIT Press, 1999).
  • J. Weston, "Leave-One-Out Support Vector Machines". IJCAI'99.
  • C. Saunders, M. O. Stitson, J. Weston, L. Bottou, B. Schoelkopf, A. Smola, "Support Vector Machine Reference Manual", CSD-TR-98-03, Royal Holloway, University of London, Egham, UK, 1998.
  • M. O. Stitson, A Gammerman, V. Vapnik, V.Vovk, C. Watkins, J. Weston, "Support Vector ANOVA decomposition". Chapter 17, Advances in Kernel Methods - Support Vector Learning", MIT Press, 1998.
  • J. Weston and C. Watkins, "Support Vector Machines for Multi-Class Pattern Recognition". ESANN'99. ( There was also a Royal Holloway Technical report CSD-TR-98-04, 1998).
  • J. Weston, A. Gammerman, M. O. Stitson, V. Vapnik, V. Vovk and C. Watkins, "Support Vector Density Estimation". Chapter 18, Advances in Kernel Methods - Support Vector Learning", MIT Press, 1998. ( There was also a Royal Holloway Technical report CSD-TR-97-23, 1997).