Valerio Perrone
Valerio Perrone
Applied Science Manager, Amazon
Potvrđena adresa e-pošte na - Početna stranica
Scalable hyperparameter transfer learning
V Perrone, R Jenatton, MW Seeger, C Archambeau
Advances in Neural Information Processing Systems, 6845-6855, 2018
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
J Chan, V Perrone, JP Spence, PA Jenkins, S Mathieson, YS Song
Advances in Neural Information Processing Systems, 8603-8614, 2018
Learning search spaces for bayesian optimization: Another view of hyperparameter transfer learning
V Perrone, H Shen, M Seeger, C Archambeau, R Jenatton
Advances in Neural Information Processing Systems, 2019
Poisson Random Fields for Dynamic Feature Models
V Perrone, PA Jenkins, D Spano, YW Teh
Journal of Machine Learning Research 18 (127), 1-45, 2017
Amazon SageMaker Autopilot: a white box AutoML solution at scale
P Das, V Perrone, N Ivkin, T Bansal, Z Karnin, H Shen, I Shcherbatyi, ...
Proceedings of the Fourth International Workshop on Data Management for End …, 2020
Fair Bayesian Optimization
V Perrone, M Donini, K Kenthapadi, C Archambeau
AAAI/ACM Conference on AI, Ethics, and Society (AIES '21), 2020
Relativistic Monte Carlo
X Lu*, V Perrone*, L Hasenclever, YW Teh, SJ Vollmer, (*joint first author)
Proceedings of the 20th International Conference on Artificial Intelligence …, 2017
GASC: Genre-Aware Semantic Change for Ancient Greek
V Perrone, M Palma, S Hengchen, A Vatri, JQ Smith, B McGillivray
ACL International Workshop on Computational Approaches to Historical …, 2019
A Quantile-based Approach for Hyperparameter Transfer Learning
D Salinas, H Shen, V Perrone
International Conference on Machine Learning 2020, 7706--7716, 2019
Cost-aware Bayesian optimization
EH Lee, V Perrone, C Archambeau, M Seeger
arXiv preprint arXiv:2003.10870, 2020
Constrained Bayesian Optimization with Max-Value Entropy Search
V Perrone, I Shcherbatyi, R Jenatton, C Archambeau, M Seeger
Advances in Neural Information Processing Systems Workshop on Meta-Learning, 2019
Amazon sagemaker automatic model tuning: Scalable gradient-free optimization
V Perrone, H Shen, A Zolic, I Shcherbatyi, A Ahmed, T Bansal, M Donini, ...
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
Multiple adaptive Bayesian linear regression for scalable Bayesian optimization with warm start
V Perrone, R Jenatton, M Seeger, C Archambeau
Advances in Neural Information Processing Systems Workshop on Meta-Learning, 2017
Multi-objective multi-fidelity hyperparameter optimization with application to fairness
R Schmucker, M Donini, V Perrone, C Archambeau
A nonmyopic approach to cost-constrained Bayesian optimization
EH Lee, D Eriksson, V Perrone, M Seeger
Uncertainty in Artificial Intelligence, 568-577, 2021
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution
A Makarova, H Shen, V Perrone, A Klein, JB Faddoul, A Krause, ...
ICLR Workshop on Neural Architecture Search 2021, 2021
Pareto-efficient Acquisition Functions for Cost-Aware Bayesian Optimization
G Guinet, V Perrone, C Archambeau
arXiv preprint arXiv:2011.11456, 2020
Syne tune: A library for large scale hyperparameter tuning and reproducible research
D Salinas, M Seeger, A Klein, V Perrone, M Wistuba, C Archambeau
International Conference on Automated Machine Learning, 16/1-23, 2022
Flexible and efficient inference with particles for the variational Gaussian approximation
T Galy-Fajou, V Perrone, M Opper
Entropy 23 (8), 990, 2021
A multi-objective perspective on jointly tuning hardware and hyperparameters
D Salinas, V Perrone, O Cruchant, C Archambeau
arXiv preprint arXiv:2106.05680, 2021
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