Zobrazeno 1 - 10
of 27 814
pro vyhledávání: '"A, Mondelli"'
Autor:
de Mello Alcantara Garrido, Lorena, Rodrigues Magalhaes, Ana Paula, Díaz Mamani, Mauro Elisban, Mondelli, José
Publikováno v:
General Dentistry; May/Jun2024, Vol. 72 Issue 3, p26-33, 8p
Autor:
Neuhaus, Jessamyn
Publikováno v:
Teaching History: A Journal of Methods; Fall2023, Vol. 48 Issue 1, p139-144, 6p
A growing number of machine learning scenarios rely on knowledge distillation where one uses the output of a surrogate model as labels to supervise the training of a target model. In this work, we provide a sharp characterization of this process for
Externí odkaz:
http://arxiv.org/abs/2410.18837
Autor:
Bombari, Simone, Mondelli, Marco
Differentially private gradient descent (DP-GD) is a popular algorithm to train deep learning models with provable guarantees on the privacy of the training data. In the last decade, the problem of understanding its performance cost with respect to s
Externí odkaz:
http://arxiv.org/abs/2410.14787
Deep neural networks (DNNs) at convergence consistently represent the training data in the last layer via a highly symmetric geometric structure referred to as neural collapse. This empirical evidence has spurred a line of theoretical research aimed
Externí odkaz:
http://arxiv.org/abs/2410.04887
Autor:
Mondelli, Marco, Venkataramanan, Ramji
We consider the problem of estimating a signal from measurements obtained via a generalized linear model. We focus on estimators based on approximate message passing (AMP), a family of iterative algorithms with many appealing features: the performanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1ae74d5cc17e8e76d5b74c64fed053a
https://www.repository.cam.ac.uk/handle/1810/346601
https://www.repository.cam.ac.uk/handle/1810/346601
We consider a prototypical problem of Bayesian inference for a structured spiked model: a low-rank signal is corrupted by additive noise. While both information-theoretic and algorithmic limits are well understood when the noise is a Gaussian Wigner
Externí odkaz:
http://arxiv.org/abs/2405.20993
Deep neural networks (DNNs) exhibit a surprising structure in their final layer known as neural collapse (NC), and a growing body of works has currently investigated the propagation of neural collapse to earlier layers of DNNs -- a phenomenon called
Externí odkaz:
http://arxiv.org/abs/2405.14468
Autor:
Zhang, Yihan, Mondelli, Marco
We study the matrix denoising problem of estimating the singular vectors of a rank-$1$ signal corrupted by noise with both column and row correlations. Existing works are either unable to pinpoint the exact asymptotic estimation error or, when they d
Externí odkaz:
http://arxiv.org/abs/2405.13912
Publikováno v:
Il Foro Italiano, 2004 Feb 01. 127(2), 405/406-409/410.
Externí odkaz:
https://www.jstor.org/stable/23200455