Valerio Perrone

553 total citations
8 papers, 60 citations indexed

About

Valerio Perrone is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and General Social Sciences. According to data from OpenAlex, Valerio Perrone has authored 8 papers receiving a total of 60 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 1 paper in General Social Sciences. Recurrent topics in Valerio Perrone's work include Machine Learning and Data Classification (6 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Machine Learning and Algorithms (2 papers). Valerio Perrone is often cited by papers focused on Machine Learning and Data Classification (6 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Machine Learning and Algorithms (2 papers). Valerio Perrone collaborates with scholars based in United Kingdom, Germany and United States. Valerio Perrone's co-authors include Cédric Archambeau, Rodolphe Jenatton, Matthias Seeger, Yee Whye Teh, Huibin Shen, Paul A. Jenkins, David Salinas, Michele Donini, Leonard Hasenclever and Manfred Opper and has published in prestigious journals such as Journal of Machine Learning Research, Entropy and Oxford University Research Archive (ORA) (University of Oxford).

In The Last Decade

Valerio Perrone

8 papers receiving 57 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Valerio Perrone United Kingdom	5	48	15	9	7	6	8	60
Wenlin Chen United States	2	26 0.5×	5 0.3×	8 0.9×	6 0.9×	2 0.3×	3	50
Johannes Oetsch Austria	6	63 1.3×	15 1.0×	6 0.7×	5 0.7×	2 0.3×	22	89
S. Akshay India	5	38 0.8×	40 2.7×	2 0.2×	4 0.6×	4 0.7×	17	61
Antoine Amarilli France	4	32 0.7×	7 0.5×	5 0.6×	17 2.4×	5 0.8×	20	48
Michael Brautbar United States	3	23 0.5×	7 0.5×	7 0.8×	3 0.4×	3 0.5×	4	48
Bangsheng Tang China	4	32 0.7×	23 1.5×	17 1.9×	5 0.7×	9 1.5×	9	68
Doug Strain United States	2	31 0.6×	14 0.9×	10 1.1×	10 1.4×	4 0.7×	3	45
Thomas Espitau France	5	61 1.3×	13 0.9×	13 1.4×	5 0.7×		13	70
Jan Leike Australia	4	36 0.8×	15 1.0×	14 1.6×		3 0.5×	11	44

Countries citing papers authored by Valerio Perrone

Since Specialization

Citations

This map shows the geographic impact of Valerio Perrone's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Valerio Perrone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Valerio Perrone more than expected).

Fields of papers citing papers by Valerio Perrone

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Valerio Perrone. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Valerio Perrone. The network helps show where Valerio Perrone may publish in the future.

Co-authorship network of co-authors of Valerio Perrone

This figure shows the co-authorship network connecting the top 25 collaborators of Valerio Perrone. A scholar is included among the top collaborators of Valerio Perrone based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Valerio Perrone. Valerio Perrone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Franceschi, Luca, Michele Donini, Valerio Perrone, et al.. (2025). Hyperparameter Optimization in Machine Learning. Florence Research (University of Florence). 18(6). 1054–1201. 1 indexed citations

2.

Perrone, Valerio, et al.. (2021). Flexible and Efficient Inference with Particles for the Variational Gaussian Approximation. Entropy. 23(8). 990–990. 3 indexed citations

3.

Donini, Michele, et al.. (2020). Multi-objective multi-fidelity hyperparameter optimization with application to fairness. 5 indexed citations

4.

Perrone, Valerio, Huibin Shen, Matthias Seeger, Cédric Archambeau, & Rodolphe Jenatton. (2019). Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning. arXiv (Cornell University). 32. 12751–12761. 8 indexed citations

5.

Salinas, David, Huibin Shen, & Valerio Perrone. (2019). A Quantile-based Approach for Hyperparameter Transfer Learning. arXiv (Cornell University). 1. 8438–8448. 3 indexed citations

6.

Perrone, Valerio, Rodolphe Jenatton, Matthias Seeger, & Cédric Archambeau. (2018). Scalable Hyperparameter Transfer Learning. Neural Information Processing Systems. 31. 6845–6855. 25 indexed citations

7.

Lu, Xiaoyu Sean, Valerio Perrone, Leonard Hasenclever, Yee Whye Teh, & Sebastian J. Vollmer. (2017). Relativistic Monte Carlo. Oxford University Research Archive (ORA) (University of Oxford). 1236–1245. 5 indexed citations

8.

Perrone, Valerio, et al.. (2016). Poisson Random Fields for Dynamic Feature Models. Journal of Machine Learning Research. 18(127). 1–45. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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