Valerio Perrone
Valerio Perrone
Senior Machine Learning Scientist, Amazon
Verified email at amazon.com - Homepage
Title
Cited by
Cited by
Year
Scalable hyperparameter transfer learning
V Perrone, R Jenatton, MW Seeger, C Archambeau
Advances in Neural Information Processing Systems, 6845-6855, 2018
792018
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
452018
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
452017
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
402017
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
372019
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
222019
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
192017
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
162020
Fair Bayesian Optimization
V Perrone, M Donini, K Kenthapadi, C Archambeau
AAAI/ACM Conference on AI, Ethics, and Society (AIES '21), 2020
142020
A Quantile-based Approach for Hyperparameter Transfer Learning
D Salinas, H Shen, V Perrone
International Conference on Machine Learning 2020, 7706--7716, 2019
142019
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
142019
Cost-aware Bayesian optimization
EH Lee, V Perrone, C Archambeau, M Seeger
arXiv preprint arXiv:2003.10870, 2020
112020
Pareto-efficient Acquisition Functions for Cost-Aware Bayesian Optimization
G Guinet, V Perrone, C Archambeau
arXiv preprint arXiv:2011.11456, 2020
72020
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization
V Perrone, H Shen, A Zolic, I Shcherbatyi, A Ahmed, T Bansal, M Donini, ...
3*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
22021
Lexical semantic change for Ancient Greek and Latin
V Perrone, S Hengchen, M Palma, A Vatri, JQ Smith, B McGillivray
Computational Approaches to Semantic Change, Language Variation, Chapter 9, 2021
22021
Multi-Objective Multi-Fidelity Hyperparameter Optimization with Application to Fairness
R Schmucker, M Donini, V Perrone, MB Zafar, C Archambeau
NeurIPS Workshop on Meta-Learning 2, 2020
22020
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
12021
Bayesian Optimization with Fairness Constraints
V Perrone, M Donini, K Kenthapadi, C Archambeau
International Conference on Machine Learning Workshop on AutoML, 0
1*
Flexible and Efficient Inference with Particles for the Variational Gaussian Approximation
T Galy-Fajou, V Perrone, M Opper
Entropy 23 (8), 990, 2021
2021
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