Perrone, Valerio

11 publications

FnTML 2025 Hyperparameter Optimization in Machine Learning Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi

TMLR 2024 Structural Pruning of Pre-Trained Language Models via Neural Architecture Search Aaron Klein, Jacek Golebiowski, Xingchen Ma, Valerio Perrone, Cedric Archambeau

AutoML 2022 Automatic Termination for Hyperparameter Optimization Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias Seeger, Cedric Archambeau

AutoML 2022 Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research David Salinas, Matthias Seeger, Aaron Klein, Valerio Perrone, Martin Wistuba, Cedric Archambeau

UAI 2021 A Nonmyopic Approach to Cost-Constrained Bayesian Optimization Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias Seeger

ICML 2020 A Quantile-Based Approach for Hyperparameter Transfer Learning David Salinas, Huibin Shen, Valerio Perrone

NeurIPS 2019 Learning Search Spaces for Bayesian Optimization: Another View of Hyperparameter Transfer Learning Valerio Perrone, Huibin Shen, Matthias W Seeger, Cedric Archambeau, Rodolphe Jenatton

NeurIPS 2018 A Likelihood-Free Inference Framework for Population Genetic Data Using Exchangeable Neural Networks Jeffrey Chan, Valerio Perrone, Jeffrey Spence, Paul Jenkins, Sara Mathieson, Yun Song

NeurIPS 2018 Scalable Hyperparameter Transfer Learning Valerio Perrone, Rodolphe Jenatton, Matthias W Seeger, Cedric Archambeau

JMLR 2017 Poisson Random Fields for Dynamic Feature Models Valerio Perrone, Paul A. Jenkins, Dario Spanò, Yee Whye Teh

AISTATS 2017 Relativistic Monte Carlo Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer