sequential optimization

Ax: A Platform for Adaptive Experimentation AutoML 2025 Scalable Acceleration for Classification-Based Derivative-Free Optimization AAAI 2025 Cylindrical Thompson Sampling for High-Dimensional Bayesian Optimization AISTATS 2024 Non-monotone Sequential Submodular Maximization AAAI 2024 Online Stackelberg Optimization via Nonlinear Control COLT 2024 RL-SeqISP: Reinforcement Learning-Based Sequential Optimization for Image Signal Processing AAAI 2024 On the Sublinear Regret of GP-UCB NeurIPS 2023 Recipe2Video: Synthesizing Personalized Videos From Recipe Texts WACV 2023 Adversarial Attacks on Gaussian Process Bandits ICML 2022 An Online Learning Approach to Sequential User-Centric Selection Problems AAAI 2022 High-dimensional Additive Gaussian Processes under Monotonicity Constraints NeurIPS 2022 Nearly Optimal Algorithms for Level Set Estimation AISTATS 2022 On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization AISTATS 2022 Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes AISTATS 2022 Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times ICML 2022 SnAKe: Bayesian Optimization with Pathwise Exploration NeurIPS 2022 Uncertainty Quantification for Bayesian Optimization AISTATS 2022 On Multi-Armed Bandit Designs for Dose-Finding Trials JMLR 2021 The Maximin Support Method: An Extension of the D’Hondt Method to Approval-Based Multiwinner Elections AAAI 2021 Active Learning of Conditional Mean Embeddings via Bayesian Optimisation UAI 2020 Bayesian Optimization of Risk Measures NeurIPS 2020 Experimental Design for Optimization of Orthogonal Projection Pursuit Models AAAI 2020 FrugalML: How to use ML Prediction APIs more accurately and cheaply NeurIPS 2020 Lower Bounds for Parallel and Randomized Convex Optimization COLT 2019 HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step AISTATS 2018