Silvia Villa

1.3k total citations
48 papers, 564 citations indexed

About

Silvia Villa is a scholar working on Computational Mechanics, Mathematical Physics and Computational Theory and Mathematics. According to data from OpenAlex, Silvia Villa has authored 48 papers receiving a total of 564 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computational Mechanics, 21 papers in Mathematical Physics and 14 papers in Computational Theory and Mathematics. Recurrent topics in Silvia Villa's work include Sparse and Compressive Sensing Techniques (26 papers), Numerical methods in inverse problems (21 papers) and Optimization and Variational Analysis (13 papers). Silvia Villa is often cited by papers focused on Sparse and Compressive Sensing Techniques (26 papers), Numerical methods in inverse problems (21 papers) and Optimization and Variational Analysis (13 papers). Silvia Villa collaborates with scholars based in Italy, United States and France. Silvia Villa's co-authors include Lorenzo Rosasco, Saverio Salzo, Alessandro Verri, Sofia Mosci, Luca Baldassarre, Matteo Santoro, Bằng Công Vũ, Veronica Umanità, Ernesto De Vito and Laura Levaggi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Machine Learning Research and Mathematical Programming.

In The Last Decade

Silvia Villa

42 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Silvia Villa Italy 13 288 164 139 126 125 48 564
Bằng Công Vũ France 10 440 1.5× 69 0.4× 345 2.5× 279 2.2× 202 1.6× 20 682
Venkat Chandrasekaran United States 11 214 0.7× 184 1.1× 101 0.7× 83 0.7× 16 0.1× 27 589
Yuly Makovoz United States 5 133 0.5× 177 1.1× 83 0.6× 170 1.3× 47 0.4× 6 558
Yuyuan Ouyang United States 5 243 0.8× 141 0.9× 104 0.7× 134 1.1× 34 0.3× 17 348
Damek Davis United States 8 202 0.7× 55 0.3× 197 1.4× 176 1.4× 89 0.7× 32 406
Keyvan Amini Iran 16 206 0.7× 84 0.5× 268 1.9× 490 3.9× 41 0.3× 44 657
Arkadi Nemirovsky Russia 7 210 0.7× 235 1.4× 163 1.2× 182 1.4× 35 0.3× 8 545
Ursula Molter Argentina 15 138 0.5× 61 0.4× 78 0.6× 24 0.2× 180 1.4× 53 639
Michel Ledoux France 3 149 0.5× 177 1.1× 76 0.5× 76 0.6× 304 2.4× 5 900
Gaetano Zanghirati Italy 8 169 0.6× 151 0.9× 71 0.5× 123 1.0× 47 0.4× 21 474

Countries citing papers authored by Silvia Villa

Since Specialization
Citations

This map shows the geographic impact of Silvia Villa'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 Silvia Villa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvia Villa more than expected).

Fields of papers citing papers by Silvia Villa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Silvia Villa. 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 Silvia Villa. The network helps show where Silvia Villa may publish in the future.

Co-authorship network of co-authors of Silvia Villa

This figure shows the co-authorship network connecting the top 25 collaborators of Silvia Villa. A scholar is included among the top collaborators of Silvia Villa 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 Silvia Villa. Silvia Villa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Themelis, Andreas, et al.. (2025). On the Convergence of Proximal Gradient Methods for Convex Simple Bilevel Optimization. Journal of Optimization Theory and Applications. 204(3).
2.
Vito, Ernesto De, et al.. (2024). On learning the optimal regularization parameter in inverse problems. Inverse Problems. 40(12). 125004–125004.
3.
Villa, Silvia, et al.. (2024). Unrolled Deep Networks for Sparse Signal Restoration in Analytical Chemistry. SPIRE - Sciences Po Institutional REpository. 1–6.
4.
Rosasco, Lorenzo, et al.. (2024). Iterative regularization for low complexity regularizers. Numerische Mathematik. 156(2). 641–689. 1 indexed citations
5.
Salzo, Saverio, et al.. (2024). Variance Reduction Techniques for Stochastic Proximal Point Algorithms. Journal of Optimization Theory and Applications. 203(2). 1910–1939. 1 indexed citations
6.
Salzo, Saverio, et al.. (2023). Convergence of an asynchronous block-coordinate forward-backward algorithm for convex composite optimization. Computational Optimization and Applications. 86(1). 303–344. 1 indexed citations
7.
Glineur, François, et al.. (2023). Snacks: a fast large-scale kernel SVM solver. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1–6.
8.
Rosasco, Lorenzo, et al.. (2022). Convergence of the forward-backward algorithm: beyond the worst-case with the help of geometry. arXiv (Cornell University). 12 indexed citations
9.
Steven, Alison, Silvia Rossi, Nicoletta Dasso, et al.. (2022). A qualitative exploration of undergraduate nursing students' experience of emotional safety for learning during their clinical practice. Nurse Education Today. 121. 105673–105673. 16 indexed citations
10.
Salzo, Saverio & Silvia Villa. (2021). Parallel random block-coordinate forward–backward algorithm: a unified convergence analysis. CINECA IRIS Institutial Research Information System (University of Genoa). 7 indexed citations
11.
Combettes, Patrick L., Saverio Salzo, & Silvia Villa. (2018). Regularized learning schemes in feature Banach spaces. IRIS Research product catalog (Sapienza University of Rome). 9 indexed citations
12.
Rosasco, Lorenzo, et al.. (2017). Thresholding gradient methods in Hilbert spaces: support identification\n and linear convergence. arXiv (Cornell University). 4 indexed citations
13.
Themelis, Andreas, Silvia Villa, Panagiotis Patrinos, & Alberto Bemporad. (2016). Stochastic gradient methods for stochastic model predictive control. Lirias (KU Leuven). 154–159. 2 indexed citations
14.
Rosasco, Lorenzo & Silvia Villa. (2015). Learning with incremental iterative regularization. CINECA IRIS Institutial Research Information System (University of Genoa). 28. 1630–1638. 15 indexed citations
15.
Vito, Ernesto De, Veronica Umanità, & Silvia Villa. (2012). An extension of Mercer theorem to matrix-valued measurable kernels. Applied and Computational Harmonic Analysis. 34(3). 339–351. 21 indexed citations
16.
Villa, Silvia, Lorenzo Rosasco, Sofia Mosci, & Alessandro Verri. (2010). Consistency of learning algorithms using Attouch–Wets convergence. Optimization. 61(3). 287–305. 3 indexed citations
17.
Rosasco, Lorenzo, Matteo Santoro, Sofia Mosci, Alessandro Verri, & Silvia Villa. (2010). A Regularization Approach to Nonlinear Variable Selection. CINECA IRIS Institutial Research Information System (University of Genoa). 653–660. 9 indexed citations
18.
Mosci, Sofia, Silvia Villa, Alessandro Verri, & Lorenzo Rosasco. (2010). A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups. CINECA IRIS Institutial Research Information System (University of Genoa). 23. 2604–2612. 29 indexed citations
19.
Lucchetti, Roberto, et al.. (2008). Generic well posedness in linear programming. CINECA IRIS Institutial Research Information System (University of Genoa). 4. 513–525. 2 indexed citations
20.
Villa, Silvia & Fioravante Patrone. (2008). Incentive compatibility in kidney exchange problems. Health Care Management Science. 12(4). 351–362. 5 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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