activity
20192026
most citedAsymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima's Replica Formula)

30 citations · 114 across the 12 of their papers we have counts for

collaborators

12 papers

q-bio.PE2026

Promotion of cooperation in deme-structured populations with growth-merging dynamics

Damien Ribière, Alia Abbara, Anne-Florence Bitbol

The spatial structure of populations may promote the emergence and maintenance of cooperation. Cooperation in the prisoner's dilemma is favored under specific update rules in evolu…

q-bio.PE2025

Environment heterogeneity creates fast amplifiers of natural selection in graph-structured populations

Cecilia Fruet, Arthur Alexandre, Alia Abbara +2

Complex spatial structure, with partially isolated subpopulations, and environment heterogeneity, such as gradients in nutrients, oxygen, and drugs, both shape the evolution of nat…

q-bio.PE2024★ 6 cited

Bridging Wright-Fisher and Moran models

Arthur Alexandre, Alia Abbara, Cecilia Fruet +2

The Wright-Fisher model and the Moran model are both widely used in population genetics. They describe the time evolution of the frequency of an allele in a well-mixed population w…

q-bio.PE2024★ 1 cited

Impact of phylogeny on the inference of functional sectors from protein sequence data

Nicola Dietler, Alia Abbara, Subham Choudhury +1

Statistical analysis of multiple sequence alignments of homologous proteins has revealed groups of coevolving amino acids called sectors. These groups of amino-acid sites feature c…

q-bio.PE2024★ 12 cited

Mutant fate in spatially structured populations on graphs: connecting models to experiments

Alia Abbara, Lisa Pagani, Celia García-Pareja +1

In nature, most microbial populations have complex spatial structures that can affect their evolution. Evolutionary graph theory predicts that some spatial structures modelled by p…

q-bio.PE2023★ 10 cited

Evolution of cooperation in deme-structured populations on graphs

Alix Moawad, Alia Abbara, Anne-Florence Bitbol

Understanding how cooperation can evolve in populations despite its cost to individual cooperators is an important challenge. Models of spatially structured populations with one in…

q-bio.PE2023★ 17 cited

Frequent asymmetric migrations suppress natural selection in spatially structured populations

Alia Abbara, Anne-Florence Bitbol

Natural microbial populations often have complex spatial structures. This can impact their evolution, in particular the ability of mutants to take over. While mutant fixation proba…

stat.ML2020★ 30 cited

Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima's Replica Formula)

Cedric Gerbelot, Alia Abbara, Florent Krzakala

There has been a recent surge of interest in the study of asymptotic reconstruction performance in various cases of generalized linear estimation problems in the teacher-student se…

stat.ML2020★ 18 cited

Asymptotic errors for convex penalized linear regression beyond Gaussian matrices

Cédric Gerbelot, Alia Abbara, Florent Krzakala

We consider the problem of learning a coefficient vector in from noisy linear observations in in the high dimensional limit to infinity w…

cond-mat.dis-nn2019★ 6 cited

Learning performance in inverse Ising problems with sparse teacher couplings

Alia Abbara, Yoshiyuki Kabashima, Tomoyuki Obuchi +1

We investigate the learning performance of the pseudolikelihood maximization method for inverse Ising problems. In the teacher-student scenario under the assumption that the teache…

cond-mat.dis-nn2019★ 3 cited

Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning

Alia Abbara, Benjamin Aubin, Florent Krzakala +1

Statistical learning theory provides bounds of the generalization gap, using in particular the Vapnik-Chervonenkis dimension and the Rademacher complexity. An alternative approach,…

stat.ML2019★ 11 cited

On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix

Alia Abbara, Antoine Baker, Florent Krzakala +1

In a noiseless linear estimation problem, one aims to reconstruct a vector x* from the knowledge of its linear projections y=Phi x*. There have been many theoretical works concentr…