40 citations · 227 across the 15 of their papers we have counts for
7 papers · 1 filter
Fair Bayesian Optimization
Valerio Perrone, Michele Donini, Muhammad Bilal Zafar +3
Given the increasing importance of machine learning (ML) in our lives, several algorithmic fairness techniques have been proposed to mitigate biases in the outcomes of the ML model…
Constrained Bayesian Optimization with Max-Value Entropy Search
Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton +2
Bayesian optimization (BO) is a model-based approach to sequentially optimize expensive black-box functions, such as the validation error of a deep neural network with respect to i…
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning
Valerio Perrone, Huibin Shen, Matthias Seeger +2
Bayesian optimization (BO) is a successful methodology to optimize black-box functions that are expensive to evaluate. While traditional methods optimize each black-box function in…
A Quantile-based Approach for Hyperparameter Transfer Learning
David Salinas, Huibin Shen, Valerio Perrone
Bayesian optimization (BO) is a popular methodology to tune the hyperparameters of expensive black-box functions. Traditionally, BO focuses on a single task at a time and is not de…
Multiple Adaptive Bayesian Linear Regression for Scalable Bayesian Optimization with Warm Start
Valerio Perrone, Rodolphe Jenatton, Matthias Seeger +1
Bayesian optimization (BO) is a model-based approach for gradient-free black-box function optimization. Typically, BO is powered by a Gaussian process (GP), whose algorithmic compl…
Poisson Random Fields for Dynamic Feature Models
Valerio Perrone, Paul A. Jenkins, Dario Spano +1
We present the Wright-Fisher Indian buffet process (WF-IBP), a probabilistic model for time-dependent data assumed to have been generated by an unknown number of latent features. T…
Relativistic Monte Carlo
Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever +2
Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCMC) algorithm that generates proposals for a Metropolis-Hastings algorithm by simulating the dynamics of a Ha…