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S. Villa

40 papers hereh-index 191.7k citations73 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author13
  • last author24

Across the 39 of 40 papers where every author was matched, so the position is known.

fields
  • math.OC25
  • stat.ML6
  • cs.LG5
  • math.ST3
  • math.FA1
same name
  • S. Villa — 102 papers
  • S. Villa — 87 papers, h 43
  • S. Villa — 6 papers
  • S. Villa — 5 papers
  • S. Villa — 5 papers
  • S. Villa — 3 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20102026
most citedNonparametric sparsity and regularization

59 citations · 195 across the 37 of their papers we have counts for

collaborators
Showing 2023 · math.OCShow all

4 papers · 2 filters

math.OC2023

Variance reduction techniques for stochastic proximal point algorithms

Cheik Traoré, Vassilis Apidopoulos, Saverio Salzo +1

In the context of finite sums minimization, variance reduction techniques are widely used to improve the performance of state-of-the-art stochastic gradient methods. Their practica…

math.OC2023

Regularization properties of dual subgradient flow

Vassilis Apidopoulos, Cesare Molinari, Lorenzo Rosasco +1

Dual gradient descent combined with early stopping represents an efficient alternative to the Tikhonov variational approach when the regularizer is strongly convex. However, for ma…

math.OC2023

An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization

Marco Rando, Cesare Molinari, Lorenzo Rosasco +1

Finite-difference methods are a class of algorithms designed to solve black-box optimization problems by approximating a gradient of the target function on a set of directions. In…

math.OC2023

On the convergence of proximal gradient methods for convex simple bilevel optimization

Puya Latafat, Andreas Themelis, Silvia Villa +1

This paper studies proximal gradient iterations for solving simple bilevel optimization problems where both the upper and the lower level cost functions are split as the sum of dif…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.