← Authors

Kevin Swersky

30 papers · 2010–2026 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (16) 🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ’Ž Century Club (30) ⚑ Prolific Year (8) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner πŸ”₯ Unstoppable (8) πŸ—ƒοΈ Keyword Collector (127)

Conferences

ICML (10) ICLR (7) NIPS (7) AISTATS (1) CVPR (1) ICCV (1) JMLR (1) UAI (1) WACV (1)

Top co-authors

Milad Hashemi (8) Daniel Tarlow (4) Parthasarathy Ranganathan (4) Jasper Snoek (4) Rich Zemel (4) Richard Zemel (3) David Duvenaud (3) Richard S. Zemel (3) Mohammad Norouzi (3) Ryan P. Adams (3)

Keywords

bayesian optimization (5) representation learning (4) gaussian process (4) generative model (3) neural network (3) hyperparameter optimization (3) multi-task learning (3) metric learning (2) zero-shot learning (2) restricted boltzmann machine (2) probabilistic model (2) distance metric (2) hyperparameter tuning (2) acquisition function (2) transfer learning (1) binary classification (1) black-box optimization (1) imitation learning (1) benchmark evaluation (1) image classification (1)

Papers

Do Generative Video Models Understand Physical Principles? WACV 2026
Pre-trained Gaussian Processes for Bayesian Optimization JMLR 2024
Directly Fine-Tuning Diffusion Models on Differentiable Rewards ICLR 2024
CUF: Continuous Upsampling Filters CVPR 2023
Data-Driven Offline Optimization for Architecting Hardware Accelerators ICLR 2022
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions ICML 2021
No MCMC for me: Amortized sampling for fast and stable training of energy-based models ICLR 2021
Amortized Bayesian Optimization over Discrete Spaces UAI 2020
An Imitation Learning Approach for Cache Replacement ICML 2020
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach ICML 2020
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples ICLR 2020
Your classifier is secretly an energy based model and you should treat it like one ICLR 2020
LEARNING EXECUTION THROUGH NEURAL CODE FUSION ICLR 2020
Neural Execution Engines: Learning to Execute Subroutines NIPS 2020
Big Self-Supervised Models are Strong Semi-Supervised Learners NIPS 2020
Graph Normalizing Flows NIPS 2019
Flexibly Fair Representation Learning by Disentanglement ICML 2019
Meta-Learning for Semi-Supervised Few-Shot Classification ICLR 2018
Learning Memory Access Patterns ICML 2018
Prototypical Networks for Few-shot Learning NIPS 2017
Generative Moment Matching Networks ICML 2015
Scalable Bayesian Optimization Using Deep Neural Networks ICML 2015
Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions ICCV 2015
Input Warping for Bayesian Optimization of Non-Stationary Functions ICML 2014
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning ICML 2013
Learning Fair Representations ICML 2013
Multi-Task Bayesian Optimization NIPS 2013
Cardinality Restricted Boltzmann Machines NIPS 2012
Probabilistic n-Choose-k Models for Classification and Ranking NIPS 2012
Inductive Principles for Restricted Boltzmann Machine Learning AISTATS 2010