5 citations · 7 across the 10 of their papers we have counts for
3 papers · 1 filter
Gaussian Process regression over discrete probability measures: on the non-stationarity relation between Euclidean and Wasserstein Squared Exponential Kernels
Antonio Candelieri, Andrea Ponti, Francesco Archetti
Gaussian Process regression is a kernel method successfully adopted in many real-life applications. Recently, there is a growing interest on extending this method to non-Euclidean…
BORA: Bayesian Optimization for Resource Allocation
Antonio Candelieri, Andrea Ponti, Francesco Archetti
Optimal resource allocation is gaining a renewed interest due its relevance as a core problem in managing, over time, cloud and high-performance computing facilities. Semi-Bandit F…
Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimization
Antonio Candelieri, Andrea Ponti, Francesco Archetti
There is a consensus that focusing only on accuracy in searching for optimal machine learning models amplifies biases contained in the data, leading to unfair predictions and decis…