:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Castiglione, Cristian, Segers, Alexandre, Clement, Lieven, Risso, Davide
Format:	Preprint
Published:	2024
Subjects:	Computation Machine Learning
Online Access:	https://arxiv.org/abs/2412.20509
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

One-step corrected projected stochastic gradient descent for statistical estimation
by: Brouste, Alexandre, et al.
Published: (2023)

State-space models can learn in-context by gradient descent
by: Sushma, Neeraj Mohan, et al.
Published: (2024)

Learning single index model with gradient descent: spectral initialization and precise asymptotics
by: Chen, Yuchen, et al.
Published: (2025)

Non-negative matrix factorization algorithms generally improve topic model fits
by: Carbonetto, Peter, et al.
Published: (2021)

The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data
by: Schuster, Viktoria, et al.
Published: (2021)

Guided parallelized stochastic gradient descent for delay compensation
by: Sharma, Anuraganand
Published: (2021)

Optimal and computationally tractable lower bounds for logistic log-likelihoods
by: Anceschi, Niccolò, et al.
Published: (2024)

Gradient descent in matrix factorization: Understanding large initialization
by: Chen, Hengchao, et al.
Published: (2023)

Explainable AI model reveals disease-related mechanisms in single-cell RNA-seq data
by: Usman, Mohammad, et al.
Published: (2025)

Gradient descent with generalized Newton's method
by: Bu, Zhiqi, et al.
Published: (2024)

Gradient descent in materia through homodyne gradient extraction
by: Boon, Marcus N., et al.
Published: (2021)

Linear-cost unbiased posterior estimates for crossed effects and matrix factorization models via couplings
by: Ceriani, Paolo Maria, et al.
Published: (2024)

JojoSCL: Shrinkage Contrastive Learning for single-cell RNA sequence Clustering
by: Wang, Ziwen
Published: (2025)

Training morphological neural networks with gradient descent: some theoretical insights
by: Blusseau, Samy
Published: (2024)

The duality structure gradient descent algorithm: analysis and applications to neural networks
by: Flynn, Thomas
Published: (2017)

Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent
by: Dette, Holger, et al.
Published: (2024)

Convergence of continuous-time stochastic gradient descent with applications to deep neural networks
by: Lugosi, Gabor, et al.
Published: (2024)

Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities
by: Caprio, Rocco, et al.
Published: (2024)

Gradient descent for deep equilibrium single-index models
by: Dandapanthula, Sanjit, et al.
Published: (2025)

Training thermodynamic computers by gradient descent
by: Whitelam, Stephen
Published: (2025)

Oblivious Stochastic Composite Optimization
by: Lezane, Clément, et al.
Published: (2023)

Fast training of accurate physics-informed neural networks without gradient descent
by: Datar, Chinmay, et al.
Published: (2024)

On the global convergence of gradient descent for wide shallow models with bounded nonlinearities
by: Petit, Romain, et al.
Published: (2026)

Lower-dimensional projections of cellular expression improves cell type classification from single-cell RNA sequencing
by: Umar, Muhammad, et al.
Published: (2024)

Convergence of gradient descent for deep neural networks
by: Chatterjee, Sourav
Published: (2022)

Stochastic gradient descent for streaming linear and rectified linear systems with adversarial corruptions
by: Jeong, Halyun, et al.
Published: (2024)

Fractional-order spike-timing-dependent gradient descent for multi-layer spiking neural networks
by: Yang, Yi, et al.
Published: (2024)

Riemannian coordinate descent algorithms on matrix manifolds
by: Han, Andi, et al.
Published: (2024)

Identification and estimation for matrix time series CP-factor models
by: Chang, Jinyuan, et al.
Published: (2024)

Clustering by Denoising: Latent plug-and-play diffusion for single-cell data
by: Meier, Dominik, et al.
Published: (2025)

Singular-limit analysis of gradient descent with noise injection
by: Shalova, Anna, et al.
Published: (2024)

Fast Spawn\&Prune (FS\&P): Global convergence of stochastic conic particle gradient descent via birth/death process
by: De Castro, Yohann, et al.
Published: (2026)

Privacy-preserving data release leveraging optimal transport and particle gradient descent
by: Donhauser, Konstantin, et al.
Published: (2024)

Stochastic gradient descent in high dimensions for multi-spiked tensor PCA
by: Arous, Gérard Ben, et al.
Published: (2024)

Generalisation under gradient descent via deterministic PAC-Bayes
by: Clerico, Eugenio, et al.
Published: (2022)

New logarithmic step size for stochastic gradient descent
by: Shamaee, M. Soheil, et al.
Published: (2024)

BadGD: A unified data-centric framework to identify gradient descent vulnerabilities
by: Wang, Chi-Hua, et al.
Published: (2024)

Optimal Algorithms for Stochastic Complementary Composite Minimization
by: d'Aspremont, Alexandre, et al.
Published: (2022)

Global convergence of gradient descent for phase retrieval
by: Fougereux, Théodore, et al.
Published: (2024)

A block-coordinate descent framework for non-convex composite optimization. Application to sparse precision matrix estimation
by: Lauga, Guillaume
Published: (2026)