William L. Hamilton

2021

Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs Dora Jambor, Komal Teru, Joelle Pineau, and William L. Hamilton Proceedings of EACL. 2021. pdf (arxiv)

Do Syntax Trees Help Pre-trained Transformers Extract Information? Devendra Singh Sachan, Yuhao Zhang, Peng Qi, and William Hamilton Proceedings of EACL. 2021. pdf (arxiv)

Neural Representation and Generation for RNA Secondary Structures Zichao Yan, William L. Hamilton, and Mathieu Blanchette Proceedings of ICLR. 2021. pdf (openreview)

A Universal Representation Transformer Layer for Few-Shot Image Classification Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, and Hugo Larochelle Proceedings of ICLR. 2021. pdf (openreview)

2020

Adversarial Example Games Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, and William L. Hamilton Proceedings of NeurIPS. 2020. pdf (arxiv)

Learning Dynamic Belief Graphs to Generalize on Text-Based Games Ashutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikuláš Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, and William L. Hamilton Proceedings of NeurIPS. 2020. pdf (arxiv)

Graph Representation Learning William L. Hamilton Morgan and Claypool Publishers. 2020. pdf

Distilling Structured Knowledge for Text-Based Relational Reasoning Jin Dong, Marc-Antoine Rondeau, and William L. Hamilton Proceedings of EMNLP. 2020.

TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung, and William L. Hamilton Proceedings of EMNLP. 2020.

Structure Aware Negative Sampling in Knowledge Graphs Kian Ahrabian, Aarash Feizi, Yasmin Salehi, William L. Hamilton, and Avishek Joey Bose Proceedings of EMNLP. 2020.

Latent Variable Modelling with Hyperbolic Normalizing Flows Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, and William L. Hamilton Proceedings of ICML. 2020. pdf (arxiv)

Inductive Relation Prediction by Subgraph Reasoning Komal K. Teru, Etienne Denis, and William L. Hamilton Proceedings of ICML. 2020. pdf

Augmented base pairing networks encode RNA-small molecule binding preferences Carlos G. Oliver, Roman Gendron, Nicolas Moitessier, Vincent Mallet, Vladimir Reinharz, William L. Hamilton, Nicolas Moitessier, and Jérôme Waldispühl Nucleic Acids Research (NAR). 2020. pdf (biorxiv)

Learning an Unreferenced Metric for Online Dialogue Evaluation Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, and Joelle Pineau Proceedings of ACL. 2020. pdf (arxiv)

Exploring the Limits of Simple Learners in Knowledge Distillation for Document Classification Ashutosh Adhikari, Achyudh Ram, Raphael Tang, William L. Hamilton, and Jimmy Lin ACL Workshop on Representation Learning for NLP. 2020.

Exploring Structural Inductive Biases in Emergent Communication Agnieszka Słowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, and Christopher Pal AAMAS Workshop on Adaptive and Learning Agents. 2020. pdf (arxiv)

Graph Neural Representational Learning of RNA Secondary Structures for Predicting RNA-Protein Interactions Zichao Yan, William L. Hamilton, and Mathieu Blanchette Proceedings of ISMB. 2020. pdf (bioarxiv)

Towards Graph Representation Learning in Emergent Communication Agnieszka Słowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, and Sean B. Holden AAAI Workshop on Reinforcement Learning in Games. 2020. pdf (arxiv)

2019

Meta-Graph: Few shot Link Prediction via Meta-Learning Avishek Joey Bose, Ankit Jain, Piero Molino, and William L. Hamilton NeurIPS Graph Representation Learning Workshop 2019. pdf (arxiv)

CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, and William L. Hamilton Proceedings of EMNLP. 2019. pdf (arxiv)

Efficient Graph Generation with Graph Recurrent Attention Networks Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, ,William L. Hamilton, David Duvenaud, Raquel Urtasun, and Richard S Zemel Proceedings of NeurIPS. 2019. pdf (arxiv)

Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia Charles C. Onu, Jonathan Lebensold, William L. Hamilton, and Doina Precup Interspeech. 2019.

Compositional Fairness Constraints for Graph Embeddings Avishek Joey Bose and William L. Hamilton Proceedings of ICML. 2019. pdf (arxiv)

Discrete Off-policy Policy Gradients Using Continuous Relaxations Andre Cianflone, Zafarali Ahmed, Riashat Islam, Avishek Joey Bose, and William L. Hamilton Proceedings of RLDM. 2019.

Neural Transfer Learning for Cry-based Diagnosis of Perinatal Asphyxia Charles C. Onu, Jonathan Lebensold, William L. Hamilton, and Doina Precup ICLR AI for Social Good Workshop. 2019.

Tutorial on Graph Representation Learning William L. Hamilton and Jian Tang AAAI Tutorial Forum. 2019. slides (zip)

Deep Graph Infomax Petar Velickovic, William Fedus, William L. Hamilton, Pietro Lio, Yoshua Bengio, and R Devon Hjelm.   Proceedings of ICLR. 2019. pdf (arxiv)

Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks Christoper Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen, Gaurav Rattan, and Martin Grohe.   Proceedings of AAAI. 2019. pdf (arxiv)

2018

Hierarchical Graph Representation Learning with Differentiable Pooling Jiaxuan You, Rex Ying, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec.   Proceedings of NeurIPS. 2018. pdf (arxiv)

Embedding Logical Queries on Knowledge Graphs William L. Hamilton, Marinka Zitnik, Payal Bajaj, Dan Jurafsky, Jure Leskovec.   Proceedings of NeurIPS. 2018. pdf (arxiv)

Compositional Fairness Constraints for Graph Embeddings Joey Bose and William L. Hamilton. NeurIPS Relational Representation Learning Workshop. 2018.

Compositional Language Understanding with Text-based Relational Reasoning Koustuv Sinha, Shagun Sodhani, William L. Hamilton, and Joelle Pineau.   NeurIPS Relational Representation Learning Workshop. 2018.

Deep Graph Infomax Petar Velickovic, William Fedus, William L. Hamilton, Pietro Lio, Yoshua Bengio, and R Devon Hjelm.   NeurIPS Relational Representation Learning Workshop. 2018.

GraphRNN: A Deep Generative Model for Graphs Jiaxuan You, Rex Ying, Xiang Ren, William L. Hamilton, Jure Leskovec.   Proceedings of ICML. 2018. pdf (arxiv)

Graph Convolutional Neural Networks for Web-scale Recommender Systems Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec.   Proceedings of KDD. 2018. pdf (arxiv)

Community Interaction and Conflict on the Web Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky.       Proceedings of The Web Conference (WWW). 2018. pdf (arxiv)   project website (code + data)

2017

Representation Learning on Graphs: Methods and Applications William L. Hamilton, Rex Ying, Jure Leskovec. IEEE Data Engineering Bulletin. 2017. pdf

Inductive Representation Learning on Large Graphs William L. Hamilton*, Rex Ying*, Jure Leskovec. Proceedings of NeurIPS. 2017. pdf     project website (code+data)

Community Identity and User Engagement in a Multi-Community Landscape Justine Zhang*, William L. Hamilton*, Cristian Danescu-Niculescu-Mizil, Jure Leskovec, Dan Jurafsky. Proceedings of ICWSM. 2017. pdf

Loyalty in Online Communities William L. Hamilton*, Justine Zhang*, Cristian Danescu-Niculescu-Mizil, Jure Leskovec, Dan Jurafsky. Proceedings of ICWSM (short paper). 2017. pdf

Language from Police Body Camera Footage Shows Racial Disparities in Officer Respect Rob Voigt, Nicholas P. Camp, Vinod Prabhakaran, William L. Hamilton, Rebecca C. Hetey, Camilla M. Griffiths, David Jurgens, Dan Jurafsky, and Jennifer L. Eberhardt. Proceedings of the National Academy of Science (PNAS). 2017. pdf

2016

Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora William L. Hamilton, Kevin Clark, Jure Leskovec, Dan Jurafsky. Proceedings of EMNLP. 2016. pdf     project website (code+data)

Cultural Shift or Linguistic Drift? Comparing Two Computational Models of Semantic Change William L. Hamilton, Jure Leskovec, Dan Jurafsky. Proceedings of EMNLP. 2016. pdf     project website (code+data)

Learning Linguistic Descriptors of User Roles in Online Communities   Alex Wang, William L. Hamilton, Jure Leskovec. EMNLP Workshop on Computational Social Science (NLP+CSS). 2016. pdf

Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change William L. Hamilton, Jure Leskovec, Dan Jurafsky. Proceedings of ACL. 2016. pdf     project website (code+data)

Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing Vinodkumar Prabhakaran, William L. Hamilton, Dan McFarland, Dan Jurafsky. Proceedings of ACL. 2016. pdf

2014

Compressed Predictive State Representation: An Efficient Moment-Method for Sequence Prediction and Sequential Decision Making William L. Hamilton MSc Thesis. McGill University. Canadian AI Association (CAIAC) 2014 MSc Thesis Award pdf

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison Borja Balle*, William L. Hamilton*, Joelle Pineau   Proceedings of ICML. 2014. pdf

Efficient Learning and Planning with Compressed Predictive States   William L. Hamilton, Mahdi Milani Fard, Joelle Pineau. Journal of Machine Learning Research (JMLR). 2014. pdf  code

2013

Modelling Sparse Dynamical Systems with Compressed Predictive State Representations William L. Hamilton, Mahdi Milani Fard, Joelle Pineau. Proceedings of ICML. 2013. pdf  code