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cs.LG2025
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
Toby Boyne, Jose Pablo Folch, Robert M Lee +2
We perform Bayesian optimization using a Gaussian process perspective on Bayesian Additive Regression Trees (BART). Our BART Kernel (BARK) uses tree agreement to define a posterior…
cs.LG2024
System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization
Jixiang Qing, Becky D Langdon, Robert M Lee +4
We consider the problem of optimizing initial conditions and termination time in dynamical systems governed by unknown ordinary differential equations (ODEs), where evaluating diff…
cs.LG2024
Transition Constrained Bayesian Optimization via Markov Decision Processes
Jose Pablo Folch, Calvin Tsay, Robert M Lee +6
Bayesian optimization is a methodology to optimize black-box functions. Traditionally, it focuses on the setting where you can arbitrarily query the search space. However, many rea…