Colloquium - Mickael Binois
Institution: Inria Sophia Antipolis
Title: Scaling up multi-objective Bayesian optimization
Date: February 8, 2022
Location: Zoom (Click here for meeting details)
Time: 10:20 AM - 11:10 AM Eastern Time
Bayesian optimization (BO) aims at efficiently optimizing expensive black-box functions, such as hyperparameter tuning problems in machine learning. Frequently, there is more than one objective to consider, in which case Pareto dominance is used to identify the set of optimal compromises between objectives. This task becomes increasingly complex as the number of design variables and objectives increases. In this talk we first introduce multi-objective Bayesian optimization with Gaussian processes. Then we discuss ideas to tackle a moderate to high number of variables. Finally we introduce the Kalai-Smorodinski solution, originating from game theory, to handle more than just a few objectives and describe its computation in practice. Illustrations are provided throughout on several examples.
Yuehua Cui, Professor and Director of Graduate Programs in the Department of Statistics and Probability (STT), has been named an elected Fellow of the American Statistical Association (ASA).
Huan Lei, assistant professor in the Department of Statistics and Probability (STT) is among five Michigan State University (MSU) researchers from the College of Natural Science (NatSci) who have received NSF Early CAREER Faculty Awards. Their cutting-edge research pushes the limits of science, while their devotion to education is preparing the next generation of scientists to propel their field even further. Collectively, over the next five years (2022-2027) they will receive more than $3.7 million in National Science Foundation (NSF) funding.
Sikta Das Adhikari, in her third year with the STT PhD program, was awarded an IMPACTS fellowship for the 2021-2022 academic year. Integrated training Model in Plant And Compu-Tational Sciences (IMPACTS) is an NSF-funded program for training doctoral students to employ advanced computational/data science approaches to address grand challenges in plant biology.
Tapabrata “Taps” Maiti, MSU Foundation Professor in the Department of Statistics and Probability, was recently named an American Association for the Advancement of Science, or AAAS, fellow for his distinguished contributions to the fields of statistics and data science, particularly for contributions to data-driven discovery, and for outstanding teaching and training of the next generation of data scientists.