← Authors

Eytan Bakshy

24 papers · 2019–2025 · 6 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (15) πŸ‘₯ Mega-Team (21) πŸ”¬ Deep Specialist (17) πŸ“ˆ Trend Setter ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (75) πŸ’Ž Century Club (24) πŸ”₯ Unstoppable (7)

Conferences

NIPS (11) AISTATS (5) ICML (4) UAI (2) AUTOML (1) JMLR (1)

Top co-authors

Maximilian Balandat (15) Samuel Daulton (8) David Eriksson (8) Benjamin Letham (6) Sebastian Ament (5) Zhiyuan Jerry Lin (4) Ben Letham (4) Peter Frazier (3) Raul Astudillo (3) Andrew G Wilson (2)

Keywords

bayesian optimization (18) acquisition function (8) gaussian process (8) multi-objective optimization (5) sample efficiency (3) surrogate model (3) expected hypervolume improvement (2) uncertainty quantification (2) expected improvement (2) multi-task learning (2) hyperparameter optimization (2) black-box function (2) decision theory (2) hypervolume improvement (2) policy search (2) parallel optimization (2) hyperparameter tuning (2) numerical optimization (1) preference learning (1) black-box optimization (1)

Papers

Scalable Gaussian Processes with Latent Kronecker Structure ICML 2025
Ax: A Platform for Adaptive Experimentation AUTOML 2025
Robust Gaussian Processes via Relevance Pursuit NIPS 2024
Joint Composite Latent Space Bayesian Optimization ICML 2024
Response Time Improves Gaussian Process Models for Perception and Preferences UAI 2024
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes NIPS 2024
Sparse Bayesian optimization AISTATS 2023
qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization AISTATS 2023
Unexpected Improvements to Expected Improvement for Bayesian Optimization NIPS 2023
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information ICML 2023
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings AISTATS 2023
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes AISTATS 2022
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization NIPS 2022
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation AISTATS 2022
Robust Multi-Objective Bayesian Optimization Under Input Noise ICML 2022
Multi-objective Bayesian optimization over high-dimensional search spaces UAI 2022
Bayesian Optimization with High-Dimensional Outputs NIPS 2021
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement NIPS 2021
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs NIPS 2021
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization NIPS 2020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization NIPS 2020
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization NIPS 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization NIPS 2020
Bayesian Optimization for Policy Search via Online-Offline Experimentation JMLR 2019