Kevin Swersky - Concepedia

Author

Kevin Swersky

University of Toronto

Also Known As

Blyth, Tim, Hashemi, Milad, Hron, Jiri, Kevin Swersky, Oztireli, Cengiz, Swersky, Kevin, Zhou, Wenlei

Publications

18.2K

Citations

H-Index

Concepts

All Affiliations

University of Toronto Google (United States)Canadian Institute for Advanced Research Harvard University University of British Columbia

About

Kevin Swersky is an author at University of Toronto specializing in engineering, computer science, and data science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	25	32	9.9K
2	Computer Science	25	32	9.9K
3	Computer Engineering	4	4	216
4	Cognitive Science	2	2	169
5	Management	1	1	116

Kevin Swersky

Publications

12K

Citations

H-Index

Page 1

	Year	Citations
Prototypical Networks for Few-shot Learning Jake Snell, Kevin Swersky, Richard S. Zemel arXiv (Cornell University) Artificial IntelligenceFew-shot LearningEngineeringMachine LearningData Science	2017	5.2K
Learning Fair Representations Rich Zemel, Yu Wu, Kevin Swersky,	2013	992
Meta-Learning for Semi-Supervised Few-Shot Classification Mengye Ren, Eleni Triantafillou, Sachin Ravi, arXiv (Cornell University) Artificial IntelligenceFew-shot LearningMultiple Instance LearningEngineeringMachine Learning	2018	726
Big Self-Supervised Models are Strong Semi-Supervised Learners Ting Chen, Simon Kornblith, Kevin Swersky, arXiv (Cornell University) Artificial IntelligenceFew-shot LearningConvolutional Neural NetworkEngineeringMachine Learning	2020	476
Multi-Task Bayesian Optimization Kevin Swersky, Jasper Snoek, Ryan P. Adams	2013	451
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek, Oren Rippel, Kevin Swersky, arXiv (Cornell University) Artificial IntelligenceModel OptimizationHyperparameter EstimationMachine VisionMachine Learning	2015	439
Generative Moment Matching Networks Yujia Li, Kevin Swersky, Rich Zemel arXiv (Cornell University) Artificial IntelligenceGenerative SystemEngineeringMachine LearningData Science	2015	379
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek, Oren Rippel, Kevin Swersky, arXiv (Cornell University) Artificial IntelligenceModel OptimizationHyperparameter EstimationMachine VisionMachine Learning	2015	376
Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions Jimmy Ba, Kevin Swersky, Sanja Fidler, Natural Language ProcessingFew-shot LearningVisual CategoriesComputer VisionMachine Learning	2015	336
The Variational Fair Autoencoder Christos Louizos, Kevin Swersky, Yujia Li, Data Archiving and Networked Services (DANS) Latent RepresentationLatent ModelingSensitive FactorsMachine LearningData Science	2016	271

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