34 citations · 100 across the 25 of their papers we have counts for
5 papers · 1 filter
Bayesian Optimization over Permutation Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa +1
Optimizing expensive to evaluate black-box functions over an input space consisting of all permutations of d objects is an important problem with many real-world applications. For…
Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization
Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa
We consider the problem of black-box multi-objective optimization (MOO) using expensive function evaluations (also referred to as experiments), where the goal is to approximate the…
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces
Aryan Deshwal, Janardhan Rao Doppa
We consider the problem of optimizing combinatorial spaces (e.g., sequences, trees, and graphs) using expensive black-box function evaluations. For example, optimizing molecules fo…
Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa
We consider the problem of optimizing hybrid structures (mixture of discrete and continuous input variables) via expensive black-box function evaluations. This problem arises in ma…
Learning Pareto-Frontier Resource Management Policies for Heterogeneous SoCs: An Information-Theoretic Approach
Aryan Deshwal, Syrine Belakaria, Ganapati Bhat +2
Mobile system-on-chips (SoCs) are growing in their complexity and heterogeneity (e.g., Arm's Big-Little architecture) to meet the needs of emerging applications, including games an…