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Bayesian Optimization

102 directly classified papers

Papers per year

Papers

High Dimensional Level Set Estimation with Bayesian Neural Network AAAI 2021
Cost-aware Graph Generation: A Deep Bayesian Optimization Approach AAAI 2021
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees NIPS 2020
Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous Bandits NIPS 2020
Gradient-Based Optimization for Bayesian Preference Elicitation AAAI 2020
GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning AAAI 2020
Experimental Design for Optimization of Orthogonal Projection Pursuit Models AAAI 2020
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems NIPS 2019
Semi-Parametric Sampling for Stochastic Bandits with Many Arms AAAI 2019
Striking the Right Balance With Uncertainty CVPR 2019
SpHMC: Spectral Hamiltonian Monte Carlo AAAI 2019
Safe Exploration for Interactive Machine Learning NIPS 2019
Practical Two-Step Lookahead Bayesian Optimization NIPS 2019
Probabilistic Matrix Factorization for Automated Machine Learning NIPS 2018
Scalable Hyperparameter Transfer Learning NIPS 2018
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs NIPS 2018
Automating Bayesian optimization with Bayesian optimization NIPS 2018
Efficient nonmyopic batch active search NIPS 2018
Optimistic optimization of a Brownian NIPS 2018
Bayesian Model-Agnostic Meta-Learning NIPS 2018
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks NIPS 2017
Improving the Expected Improvement Algorithm NIPS 2017
Learning under uncertainty: a comparison between R-W and Bayesian approach NIPS 2016
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition NIPS 2016