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  • title: Knowing The What But Not The Where in Bayesian Optimization
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            Knowing The What But Not The Where in Bayesian Optimization
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            Knowing The What But Not The Where in Bayesian Optimization

            Jul 12, 2020

            Speakers

            VN
            VN

            Vu Nguyen

            Speaker · 3 followers

            MAO

            Michael A Osborne

            Speaker · 0 followers

            About

            Bayesian optimization has demonstrated impressive success in finding the optimum input x∗ and output f ∗ = f(x∗) = max f(x) of a black-box function f . In some applications, however, the optimum output is known in advance and the goal is to find the corresponding optimum input. Existing work in Bayesian optimization (BO) has not effectively exploited the knowledge of f ∗ for optimization. In this paper, we consider a new setting in BO in which the knowledge of the optimum output is available. Ou…

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            I2

            ICML 2020

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            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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