bayesian optimization

Time-varying Gaussian Process Bandits with Unknown Prior AISTATS 2025 Towards Comprehensive Evaluation of Open-Source Language Models: A Multi-Dimensional, User-Driven Approach ACL 2025 Transfer-Aware Data Selection for Domain Adaptation in Text Retrieval EMNLP 2025 Understanding High-Dimensional Bayesian Optimization ICML 2025 ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers ICCV 2025 Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context AISTATS 2025 Weight-Aware Activation Sparsity with Constrained Bayesian Optimization Scheduling for Large Language Models EMNLP 2025 Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models AISTATS 2025 Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo AISTATS 2024 Active Set Ordering NeurIPS 2024 Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach AISTATS 2024 Adaptive Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization EMNLP 2024 Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization AISTATS 2024 A General Framework for User-Guided Bayesian Optimization ICLR 2024 An invariant information geometric method for high-dimensional online optimization L4DC 2024 Approximation-Aware Bayesian Optimization NeurIPS 2024 Are You Concerned about Limited Function Evaluations: Data-Augmented Pareto Set Learning for Expensive Multi-Objective Optimization AAAI 2024 A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules? ICML 2024 A Study of Bayesian Neural Network Surrogates for Bayesian Optimization ICLR 2024 A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences NeurIPS 2024 Augmented Bayesian Policy Search ICLR 2024 A Unified Framework for Bayesian Optimization under Contextual Uncertainty ICLR 2024 AutoCD: Automated Machine Learning for Causal Discovery Algorithms PGM 2024 Batched Energy-Entropy acquisition for Bayesian Optimization NeurIPS 2024 Bayesian Adaptive Calibration and Optimal Design NeurIPS 2024