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Posterior Objectives
The dataset used in the paper is a set of posterior objectives, which are used to evaluate the performance of the Deterministic Langevin Optimization algorithm. -
Deterministic Langevin Optimization
The dataset used in the paper is a set of expensive black-box functions, which are maximized using the Deterministic Langevin Optimization algorithm. -
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning...
The dataset used in the paper is a synthetic game with two agents, where the payoff functions are sampled from a Gaussian process. -
Combinatorial 3D Shape Generation via Sequential Assembly
Combinatorial 3D shape generation framework using Bayesian optimization -
Bayesian Optimization for Industrial Process Optimization
The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used a Bayesian Optimization algorithm and a dataset for industrial process... -
Causal Bayesian Optimization
The dataset used in the paper is a combination of two causal graphs, one for prostate cancer study and another for statin dosage study. -
ε-greedy Thompson Sampling
Two benchmark functions (2d Ackley and 6d Rosenbrock) and a steel cantilever beam dataset -
Bananas: Bayesian Optimization with Neural Architectures for Neural Architect...
Bananas: Bayesian Optimization with Neural Architectures for Neural Architecture Search
