Yanshuai Cao

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Senior Research Team Lead

PhD Computer Science, University of Toronto

Yanshuai Cao is currently a senior research team lead at Borealis AI. His long-term research goal is to create machines that can learn from as little supervision as possible and as quickly as humans do when facing new data. Currently, his research spans generative models, continual learning, computer vision and natural language processing. Previously, he also explored Bayesian nonparametric methods to that same end.

Yanshuai received his PhD in Computer Science from the Department of Computer Science at the University of Toronto, where he was advised by Professor David J. Fleet and Professor Aaron Hertzmann.
 

Research Areas

Computer Vision

Natural Language Processing

Publications

July 12, 2020 Evaluating Lossy Compression Rates of Deep Generative Models
International Conference on Machine Learning (ICML), 2020
Authors: *S. Huang, *A. Makhzani, Y. Cao , R. Grosse
* Denotes equal contribution
July 12, 2020 On Variational Learning of Controllable Representations for Text without Supervision
International Conference on Machine Learning (ICML), 2020
Authors: P. Xu , Y. Cao
June 3, 2020 Better Long-Range Dependency by Bootstrapping A Mutual Information Regularizer
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Authors: *Y. Cao , *P. Xu
* Denotes equal contribution
July 28, 2019 A Cross-Domain Transferable Neural Coherence Model
Association for Computational Linguistics (ACL), 2019
Authors: P. Xu , H. Saghir, J. Kang , L. Long, A. J. Bose, Y. Cao
Dec. 3, 2018 Few-Shot Self Reminder to Overcome Catastrophic Forgetting
Workshop on Continual Learning (NeurIPS), 2018
Authors: J. Wen, Y. Cao , R. Huang
Dec. 3, 2018 Compositional Hard Negatives for Visual Semantic Embeddings via an Adversary
Workshop on ViGIL (NeurIPS), 2018
Authors: *A. J. Bose, *H. Ling, Y. Cao
* Denotes equal contribution
July 15, 2018 Adversarial Contrastive Estimation
Association for Computational Linguistics (ACL), 2018
Authors: *A. J. Bose, *H. Ling, *Y. Cao
* Denotes equal contribution
April 30, 2018 Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
International Conference on Learning Representations (ICLR), 2018
Authors: Y. Cao , G. W. Ding , K. Lui , R. Huang
Aug. 6, 2017 Implicit Manifold Learning on Generative Adversarial Networks
Workshop on Implicit Models (ICML), 2017
Authors: K. Lui , Y. Cao , M. Gazeau, K. S. Zhang
Aug. 6, 2017 Automatic Selection of t-SNE Perplexity
Workshop on AutoML (ICML), 2017
Authors: Y. Cao , L. Wang
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