Image de couverture de livre

Topological trivialization in non-convex empirical risk minimization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Montanari, Andrea, Saeed, Basil
Format:	Preprint
Publié:	2026
Sujets:	Statistics Theory
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Local minima of the empirical risk in high dimension: General theorems and convex examples
par: Asgari, Kiana, et autres
Publié: (2025)

A non-asymptotic theory of Kernel Ridge Regression: deterministic equivalents, test error, and GCV estimator
par: Misiakiewicz, Theodor, et autres
Publié: (2024)

Gradient descent inference in empirical risk minimization
par: Han, Qiyang, et autres
Publié: (2024)

Schrödinger bridge problem via empirical risk minimization
par: Belomestny, Denis, et autres
Publié: (2026)

Posterior Sampling in High Dimension via Diffusion Processes
par: Montanari, Andrea, et autres
Publié: (2023)

Provably Efficient Posterior Sampling for Sparse Linear Regression via Measure Decomposition
par: Montanari, Andrea, et autres
Publié: (2024)

Equivalence of Approximate Message Passing and Low-Degree Polynomials in Rank-One Matrix Estimation
par: Montanari, Andrea, et autres
Publié: (2022)

Phase Transitions for Feature Learning in Neural Networks
par: Montanari, Andrea, et autres
Publié: (2026)

The high-dimensional asymptotics of first order methods with random data
par: Celentano, Michael, et autres
Publié: (2021)

High-dimensional logistic regression with missing data: Imputation, regularization, and universality
par: Verchand, Kabir Aladin, et autres
Publié: (2024)

Estimation and inference for minimizer and minimum of convex functions: optimality, adaptivity and uncertainty principles
par: Cai, T. Tony, et autres
Publié: (2023)

Adaptive tail index estimation: minimal assumptions and non-asymptotic guarantees
par: Lederer, Johannes, et autres
Publié: (2025)

Unveiling low-dimensional patterns induced by convex non-differentiable regularizers
par: Hejný, Ivan, et autres
Publié: (2024)

A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists
par: Montanari, Andrea, et autres
Publié: (2022)

Tractability from overparametrization: The example of the negative perceptron
par: Montanari, Andrea, et autres
Publié: (2021)

Function estimation in the empirical Bayes setting
par: Kang, Benjamin, et autres
Publié: (2026)

Convergence of empirical Gromov-Wasserstein distance
par: Kato, Kengo, et autres
Publié: (2025)

The empirical discrete copula process
par: Geenens, Gery, et autres
Publié: (2025)

Worst-risk minimization in generalized structural equation models
par: Kennerberg, Philip, et autres
Publié: (2023)

General asymptotic representations of indexes based on the functional empirical process and the residual functional empirical process and applications
par: Lo, Gane Samb, et autres
Publié: (2025)

Asymptotics of constrained $M$-estimation under convexity
par: Brunel, Victor-Emmanuel
Publié: (2025)

The relation of bias with risk in empirically constrained inferences
par: Sakthivadivel, Dalton A R
Publié: (2025)

Nearly minimax empirical Bayesian prediction of independent Poisson observables
par: Li, Xiao
Publié: (2023)

Rate of convergence of the smoothed empirical Wasserstein distance
par: Block, Adam, et autres
Publié: (2022)

Dimension free ridge regression
par: Cheng, Chen, et autres
Publié: (2022)

Average quantile regression: a new non-mean regression model and coherent risk measure
par: Jiang, Rong, et autres
Publié: (2025)

Intrinsic-dimension empirical Bernstein inequalities for bounded self-adjoint operators
par: Martinez-Taboada, Diego, et autres
Publié: (2026)

Local empirical Bayes correction for Bayesian modeling
par: Hayashi, Yoshiko
Publié: (2025)

On concentration of the empirical measure for radial transport costs
par: Larsson, Martin, et autres
Publié: (2023)

On testing the class of symmetry using entropy characterization and empirical likelihood approach
par: Avhad, Ganesh Vishnu, et autres
Publié: (2025)

Consistency of empirical distributions of sequences of graph statistics in networks with dependent edges
par: Stewart, Jonathan R.
Publié: (2024)

Optimal tuning-free convex relaxation for noisy matrix completion
par: Yang, Yuepeng, et autres
Publié: (2022)

Optimal worst-risk minimization in structural equation models with random coefficients
par: Kennerberg, Philip, et autres
Publié: (2023)

Semi-supervised learning in unmatched linear regression using an empirical likelihood approach
par: Balabdaoui, Fadoua, et autres
Publié: (2026)

Wasserstein convergence rates for empirical measures of point processes
par: Huang, Dongzhou, et autres
Publié: (2026)

Concentration of the bootstrap empirical process, with applications to statistical inference
par: Maillard, Guillaume, et autres
Publié: (2026)

Exact bounds for some quadratic empirical processes with applications
par: Han, Qiyang
Publié: (2022)

On the supremum and its location of the standardized uniform empirical process
par: Ferger, Dietmar
Publié: (2025)

Generalization of the simplicial depth: no vanishment outside the convex hull of the distribution support
par: Francisci, Giacomo, et autres
Publié: (2019)

The noise barrier and the large signal bias of the Lasso and other convex estimators
par: Bellec, Pierre C
Publié: (2018)