Kyurae Kim

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 16

Top Topics

Doubly Stochastic

Variational Inference

Posterior Distribution

Top Venues

Publications

Samuel Gruffaz, Kyurae Kim, Alain Durmus, Jacob R. Gardner
Stochastic Approximation with Biased MCMC for Expectation Maximization. AISTATS (2024)
Joohwan Ko, Kyurae Kim, Woochang Kim, Jacob R. Gardner
Provably Scalable Black-Box Variational Inference with Structured Variational Families. CoRR (2024)
Kyurae Kim, Yi-An Ma, Jacob R. Gardner
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? AISTATS (2024)
Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus, Jacob R. Gardner
Stochastic Approximation with Biased MCMC for Expectation Maximization. CoRR (2024)
Natalie Maus, Kyurae Kim, Geoff Pleiss, David Eriksson, John P. Cunningham, Jacob R. Gardner
Approximation-Aware Bayesian Optimization. CoRR (2024)
Kyurae Kim, Joohwan Ko, Yi-An Ma, Jacob R. Gardner
Demystifying SGD with Doubly Stochastic Gradients. CoRR (2024)
Kyurae Kim, Yian Ma, Jacob R. Gardner
Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing? CoRR (2023)
Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob R. Gardner
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference. CoRR (2023)
Kyurae Kim, Kaiwen Wu, Jisu Oh, Yian Ma, Jacob R. Gardner
Black-Box Variational Inference Converges. CoRR (2023)
Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob Gardner
The Behavior and Convergence of Local Bayesian Optimization. NeurIPS (2023)
Kyurae Kim, Kaiwen Wu, Jisu Oh, Jacob R. Gardner
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference. ICML (2023)
Kyurae Kim, Jisu Oh, Kaiwen Wu, Yian Ma, Jacob R. Gardner
On the Convergence of Black-Box Variational Inference. NeurIPS (2023)
Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner
The Behavior and Convergence of Local Bayesian Optimization. CoRR (2023)
Kyurae Kim, Youngjae Kim, Sungyong Park
A Probabilistic Machine Learning Approach to Scheduling Parallel Loops with Bayesian Optimization. CoRR (2022)
Kyurae Kim, Jisu Oh, Jacob R. Gardner, Adji Bousso Dieng, Hongseok Kim
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients. NeurIPS (2022)
Kyurae Kim, Jisu Oh, Jacob R. Gardner, Adji Bousso Dieng, Hongseok Kim
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients. CoRR (2022)