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Bayesian Optimization

102 directly classified papers

Papers per year

Papers

PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks AAAI 2025
Expected Hypervolume Improvement Is a Particular Hypervolume Improvement AAAI 2025
CoffeeBoost: Gradient Boosting Native Conformal Inference for Bayesian Optimization AAAI 2025
Multi-Objective Molecular Design Through Learning Latent Pareto Set AAAI 2025
Offline-to-Online Hyperparameter Transfer for Stochastic Bandits AAAI 2025
Inversion-based Latent Bayesian Optimization NIPS 2024
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental Design AAAI 2024
Looping in the Human: Collaborative and Explainable Bayesian Optimization AISTATS 2024
Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal NIPS 2024
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty AISTATS 2024
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach AISTATS 2024
Batched Energy-Entropy acquisition for Bayesian Optimization NIPS 2024
Provable Posterior Sampling with Denoising Oracles via Tilted Transport NIPS 2024
Robust Gaussian Processes via Relevance Pursuit NIPS 2024
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning NIPS 2024
Grey-Box Bayesian Optimization for Sensor Placement in Assisted Living Environments AAAI 2024
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023
Are Random Decompositions all we need in High Dimensional Bayesian Optimisation? ICML 2023
High-Dimensional Dueling Optimization with Preference Embedding AAAI 2023
“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization NIPS 2023
Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking ACL 2023
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits NIPS 2023
Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction CVPR 2023
Failure-Aware Gaussian Process Optimization with Regret Bounds NIPS 2023
Meta-Learning for Simple Regret Minimization AAAI 2023