Eytan Bakshy
24 papers · 2019–2025 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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(19)
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Keyword Collector
(91)
Top co-authors
Research topics
Machine Learning
(24)
Optimization & Theory
(22)
Mathematics & Optimization
(13)
Optimization
(13)
Bayesian & Probabilistic Β· Machine Learning
(10)
Artificial Intelligence
(9)
Learning Types Β· Machine Learning
(7)
Bayesian & Probabilistic Β· Artificial Intelligence
(6)
Application Areas
(4)
Core AI
(3)
Core Methods
(2)
Data Science & Analytics
(1)
Deep Learning
(1)
Reinforcement Learning
(1)
Learning Types Β· Deep Learning
(1)
Keywords
bayesian optimization
(19)
gaussian process
(9)
acquisition function
(8)
multi-objective optimization
(5)
surrogate model
(4)
sample efficiency
(4)
black-box optimization
(2)
uncertainty quantification
(2)
expected hypervolume improvement
(2)
hyperparameter optimization
(2)
decision theory
(2)
multi-task learning
(2)
hyperparameter tuning
(2)
preference learning
(2)
sequential optimization
(2)
parallel optimization
(2)
policy search
(2)
black-box function
(2)
expected improvement
(2)
hypervolume improvement
(2)
Papers
Ax: A Platform for Adaptive Experimentation
AutoML 2025
Scalable Gaussian Processes with Latent Kronecker Structure
ICML 2025
Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
NeurIPS 2024
Joint Composite Latent Space Bayesian Optimization
ICML 2024
Response Time Improves Gaussian Process Models for Perception and Preferences
UAI 2024
Robust Gaussian Processes via Relevance Pursuit
NeurIPS 2024
Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings
AISTATS 2023
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information
ICML 2023
qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization
AISTATS 2023
Sparse Bayesian optimization
AISTATS 2023
Unexpected Improvements to Expected Improvement for Bayesian Optimization
NeurIPS 2023
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
NeurIPS 2022
Look-Ahead Acquisition Functions for Bernoulli Level Set Estimation
AISTATS 2022
Multi-objective Bayesian optimization over high-dimensional search spaces
UAI 2022
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes
AISTATS 2022
Robust Multi-Objective Bayesian Optimization Under Input Noise
ICML 2022
Bayesian Optimization with High-Dimensional Outputs
NeurIPS 2021
Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs
NeurIPS 2021
Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement
NeurIPS 2021
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization
NeurIPS 2020
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization
NeurIPS 2020
High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization
NeurIPS 2020
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
NeurIPS 2020
Bayesian Optimization for Policy Search via Online-Offline Experimentation
JMLR 2019