Valerio Perrone

32 papers A* 5A 2C 1Journal 21Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Hyperparameter Optimization in Machine Learning.
Found. Trends Mach. Learn.
Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi
2024 J jnl
Hyperparameter Optimization in Machine Learning.
CoRR
Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein, Cédric Archambeau, Matthias W. Seeger, Massimiliano Pontil, Paolo Frasconi
2024 J jnl
Structural Pruning of Pre-trained Language Models via Neural Architecture Search.
CoRR
Aaron Klein, Jacek Golebiowski, Xingchen Ma, Valerio Perrone, Cédric Archambeau
2024 J jnl
Structural Pruning of Pre-trained Language Models via Neural Architecture Search.
Trans. Mach. Learn. Res.
Aaron Klein, Jacek Golebiowski, Xingchen Ma, Valerio Perrone, Cédric Archambeau
2022 — conf
Automatic Termination for Hyperparameter Optimization.
AutoML
Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2022 — conf
Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research.
AutoML
David Salinas, Matthias W. Seeger, Aaron Klein, Valerio Perrone, Martin Wistuba, Cédric Archambeau
2021 A conf
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization.
UAI
Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger
2021 J jnl
A Nonmyopic Approach to Cost-Constrained Bayesian Optimization.
CoRR
Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger
2021 J jnl
A Simple and Fast Baseline for Tuning Large XGBoost Models.
CoRR
Sanyam Kapoor, Valerio Perrone
2021 J jnl
A multi-objective perspective on jointly tuning hardware and hyperparameters.
CoRR
David Salinas, Valerio Perrone, Olivier Cruchant, Cédric Archambeau
2021 A* conf
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization.
KDD
Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau
2021 C conf
Fair Bayesian Optimization.
AIES
Valerio Perrone, Michele Donini, Muhammad Bilal Zafar, Robin Schmucker, Krishnaram Kenthapadi, Cédric Archambeau
2021 J jnl
Flexible and Efficient Inference with Particles for the Variational Gaussian Approximation.
Entropy
Théo Galy-Fajou, Valerio Perrone, Manfred Opper
2021 J jnl
Lexical semantic change for Ancient Greek and Latin.
CoRR
Valerio Perrone, Simon Hengchen, Marco Palma, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray
2021 J jnl
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution.
CoRR
Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau
2020 A* conf
A Quantile-based Approach for Hyperparameter Transfer Learning.
ICML
David Salinas, Huibin Shen, Valerio Perrone
2020 J jnl
Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization.
CoRR
Valerio Perrone, Huibin Shen, Aida Zolic, Iaroslav Shcherbatyi, Amr Ahmed, Tanya Bansal, Michele Donini, Fela Winkelmolen, Rodolphe Jenatton, Jean Baptiste Faddoul, Barbara Pogorzelska, Miroslav Miladinovic, Krishnaram Kenthapadi, Matthias W. Seeger, Cédric Archambeau
2020 J jnl
Amazon SageMaker Autopilot: a white box AutoML solution at scale.
CoRR
Piali Das, Valerio Perrone, Nikita Ivkin, Tanya Bansal, Zohar S. Karnin, Huibin Shen, Iaroslav Shcherbatyi, Yotam Elor, Wilton Wu, Aida Zolic, Thibaut Liénart, Alex Tang, Amr Ahmed, Jean Baptiste Faddoul, Rodolphe Jenatton, Fela Winkelmolen, Philip Gautier, Leo Dirac, Andre Perunicic, Miroslav Miladinovic, Giovanni Zappella, Cédric Archambeau, Matthias W. Seeger, Bhaskar Dutt, Laurence Rouesnel
2020 J jnl
Cost-aware Bayesian Optimization.
CoRR
Eric Hans Lee, Valerio Perrone, Cédric Archambeau, Matthias W. Seeger
2020 J jnl
Fair Bayesian Optimization.
CoRR
Valerio Perrone, Michele Donini, Krishnaram Kenthapadi, Cédric Archambeau
2020 J jnl
Pareto-efficient Acquisition Functions for Cost-Aware Bayesian Optimization.
CoRR
Gauthier Guinet, Valerio Perrone, Cédric Archambeau
2019 J jnl
A Copula approach for hyperparameter transfer learning.
CoRR
David Salinas, Huibin Shen, Valerio Perrone
2019 J jnl
Constrained Bayesian Optimization with Max-Value Entropy Search.
CoRR
Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton, Cédric Archambeau, Matthias W. Seeger
2019 — conf
GASC: Genre-Aware Semantic Change for Ancient Greek.
LChange@ACL
Valerio Perrone, Marco Palma, Simon Hengchen, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray
2019 J jnl
GASC: Genre-Aware Semantic Change for Ancient Greek.
CoRR
Valerio Perrone, Marco Palma, Simon Hengchen, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray
2019 A* conf
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.
NeurIPS
Valerio Perrone, Huibin Shen
2019 J jnl
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.
CoRR
Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton
2018 A* conf
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks.
NeurIPS
Jeffrey Chan, Valerio Perrone, Jeffrey P. Spence, Paul A. Jenkins, Sara Mathieson, Yun S. Song
2018 J jnl
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks.
CoRR
Jeffrey Chan, Valerio Perrone, Jeffrey P. Spence, Paul A. Jenkins, Sara Mathieson, Yun S. Song
2018 A* conf
Scalable Hyperparameter Transfer Learning.
NeurIPS
Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cédric Archambeau
2017 J jnl
Poisson Random Fields for Dynamic Feature Models.
J. Mach. Learn. Res.
Valerio Perrone, Paul A. Jenkins, Dario Spanò, Yee Whye Teh
2017 A conf
Relativistic Monte Carlo.
AISTATS
Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer