Manuel Sáenz

Publication Activity (10 Years)

Years Active: 2018-2022
Publications (10 Years): 8

Top Topics

Learning Curves

Linear Regression

Greedy Algorithms

Top Venues

SIGMETRICS Perform. Evaluation Rev.

Publications

Jean Barbier, Francesco Camilli, Marco Mondelli, Manuel Sáenz
Bayes-optimal limits in structured PCA, and how to reach them. CoRR (2022)
Jean Barbier, Tianqi Hou, Marco Mondelli, Manuel Sáenz
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? CoRR (2022)
Jean Barbier, TianQi Hou, Marco Mondelli, Manuel Sáenz
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? NeurIPS (2022)
Matthieu Jonckheere, Manuel Sáenz
Exact asymptotic characterisation of running time for approximate gradient descent on random graphs. CoRR (2021)
Jean Barbier, Wei-Kuo Chen, Dmitry Panchenko, Manuel Sáenz
Performance of Bayesian linear regression in a model with mismatch. CoRR (2021)
Paola Bermolen, Matthieu Jonckheere, Federico Larroca, Manuel Sáenz
Sequential Algorithms and Independent Sets Discovering on Large Sparse Random Graphs. CoRR (2020)
Jean Barbier, Dmitry Panchenko, Manuel Sáenz
Strong replica symmetry for high-dimensional disordered log-concave Gibbs measures. CoRR (2020)
Paola Bermolen, Matthieu Jonckheere, Federico Larroca, Manuel Sáenz
Degree-Greedy Algorithms on Large Random Graphs. SIGMETRICS Perform. Evaluation Rev. 46 (3) (2018)