Valerio Perrone

According to our database, Valerio Perrone authored at least 26 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Syne Tune: A Library for Large Scale Hyperparameter Tuning and Reproducible Research.

David Salinas, Matthias W. Seeger, Aaron Klein, Valerio Perrone, Martin Wistuba, Cédric Archambeau

Proceedings of the International Conference on Automated Machine Learning, 2022

Automatic Termination for Hyperparameter Optimization.

Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau

Proceedings of the International Conference on Automated Machine Learning, 2022

2021

Flexible and Efficient Inference with Particles for the Variational Gaussian Approximation.

Théo Galy-Fajou, Valerio Perrone, Manfred Opper

Entropy, 2021

A Simple and Fast Baseline for Tuning Large XGBoost Models.

Sanyam Kapoor, Valerio Perrone

CoRR, 2021

A multi-objective perspective on jointly tuning hardware and hyperparameters.

David Salinas, Valerio Perrone, Olivier Cruchant, Cédric Archambeau

CoRR, 2021

Overfitting in Bayesian Optimization: an empirical study and early-stopping solution.

Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau

CoRR, 2021

Lexical semantic change for Ancient Greek and Latin.

Valerio Perrone, Simon Hengchen, Marco Palma, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray

CoRR, 2021

A Nonmyopic Approach to Cost-Constrained Bayesian Optimization.

Eric Hans Lee, David Eriksson, Valerio Perrone, Matthias W. Seeger

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization.

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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Fair Bayesian Optimization.

Valerio Perrone, Michele Donini, Muhammad Bilal Zafar, Robin Schmucker, Krishnaram Kenthapadi, Cédric Archambeau

Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

2020

Amazon SageMaker Automatic Model Tuning: Scalable Black-box Optimization.

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

CoRR, 2020

Amazon SageMaker Autopilot: a white box AutoML solution at scale.

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

CoRR, 2020

Pareto-efficient Acquisition Functions for Cost-Aware Bayesian Optimization.

Gauthier Guinet, Valerio Perrone, Cédric Archambeau

CoRR, 2020

Fair Bayesian Optimization.

Valerio Perrone, Michele Donini, Krishnaram Kenthapadi, Cédric Archambeau

CoRR, 2020

Cost-aware Bayesian Optimization.

Eric Hans Lee, Valerio Perrone, Cédric Archambeau, Matthias W. Seeger

CoRR, 2020

A Quantile-based Approach for Hyperparameter Transfer Learning.

David Salinas, Huibin Shen, Valerio Perrone

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Constrained Bayesian Optimization with Max-Value Entropy Search.

Valerio Perrone, Iaroslav Shcherbatyi, Rodolphe Jenatton, Cédric Archambeau, Matthias W. Seeger

CoRR, 2019

A Copula approach for hyperparameter transfer learning.

David Salinas, Huibin Shen, Valerio Perrone

CoRR, 2019

Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.

Valerio Perrone, Huibin Shen, Matthias W. Seeger, Cédric Archambeau, Rodolphe Jenatton

CoRR, 2019

Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning.

Valerio Perrone, Huibin Shen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

GASC: Genre-Aware Semantic Change for Ancient Greek.

Valerio Perrone, Marco Palma, Simon Hengchen, Alessandro Vatri, Jim Q. Smith, Barbara McGillivray

Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change, 2019

2018

Scalable Hyperparameter Transfer Learning.

Valerio Perrone, Rodolphe Jenatton, Matthias W. Seeger, Cédric Archambeau

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks.

Jeffrey Chan, Valerio Perrone, Jeffrey P. Spence, Paul A. Jenkins, Sara Mathieson, Yun S. Song

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Poisson Random Fields for Dynamic Feature Models.

Valerio Perrone, Paul A. Jenkins, Dario Spanò, Yee Whye Teh

J. Mach. Learn. Res., 2017

Relativistic Monte Carlo.

Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, Sebastian J. Vollmer

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

NIPS Conference Papers 1987-2015.

Valerio Perrone

Dataset, November, 2016