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Martin Jaggi

6 papers hereh-index 2407 citations8 works total

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

author position
  • middle author1
  • last author5

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • math.OC2
same name
  • Martin Jaggi — 122 papers, h 60
  • Martin Jaggi — 31 papers, h 12
  • Martin Jaggi — 16 papers, h 5
  • Martin Jaggi — 2 papers
  • Martin Jaggi — 2 papers, h 2
  • Martin Jaggi — 1 paper, h 1

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
20122026
most citedBlock-Coordinate Frank-Wolfe Optimization for Structural SVMs

152 citations · 152 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping

Hsun-Yu Kuo, El Mahdi Chayti, Patrik Reizinger +2

Looped Transformers, which repeatedly apply a shared transformer block, are an architecturally natural fit for variable-length algorithmic tasks. Although they can exhibit strong l…

cs.LG2025

α-LoRA: Effective Fine-Tuning via Base Model Rescaling

Aymane El Firdoussi, El Mahdi Chayti, Mohamed El Amine Seddik +1

Fine-tuning has proven to be highly effective in adapting pre-trained models to perform better on new desired tasks with minimal data samples. Among the most widely used approaches…

cs.LG2025

Stochastic Difference-of-Convex Optimization with Momentum

El Mahdi Chayti, Martin Jaggi

We study the online stochastic difference-of-convex (DC) program minx∈Rn​F(x)=G(x)−H(x)+r1​(x)−r2​(x), which covers sparse learning with nonconvex penalties, rob…

cs.LG2012★ 152 cited

Block-Coordinate Frank-Wolfe Optimization for Structural SVMs

Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt +1

We propose a randomized block-coordinate variant of the classic Frank-Wolfe algorithm for convex optimization with block-separable constraints. Despite its lower iteration cost, we…

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