Concept
Ridge regression
Related publications (288)
Scaling behavior of bedload transport: what if Bagnold was right?
There is a paradox in the relationship between bedload transport rates and flow variables: laboratory and field studies have reported on how bedload transport rates depend on flow variables through a power law, but none of the empirical laws fitted to the ...
2023Regularization of polynomial networks for image recognition
Volkan Cevher, Grigorios Chrysos, Bohan Wang
Deep Neural Networks (DNNs) have obtained impressive performance across tasks, however they still remain as black boxes, e.g., hard to theoretically analyze. At the same time, Polynomial Networks (PNs) have emerged as an alternative method with a promising ...
2023The statistical complexity of early-stopped mirror descent
Tomas Vaskevicius, Varun Kanade
Recently there has been a surge of interest in understanding implicit regularization properties of iterative gradient-based optimization algorithms. In this paper, we study the statistical guarantees on the excess risk achieved by early-stopped unconstrain ...
Oxford2023Regularization Techniques for Low-Resource Machine Translation
Neural machine translation (MT) and text generation have recently reached very high levels of quality. However, both areas share a problem: in order to reach these levels, they require massive amounts of data. When this is not present, they lack generaliza ...
EPFL2023Une version polyatomique de l'algorithme Frank-Wolfe pour résoudre le problème LASSO en grandes dimensions
Julien René Pierre Fageot, Adrian Thibault Etienne Jarret, Matthieu Martin Jean-André Simeoni
Nous nous intéressons à la reconstruction parcimonieuse d’images à l’aide du problème d’optimisation régularisé LASSO. Dans de nombreuses applications pratiques, les grandes dimensions des objets à reconstruire limitent, voire empêchent, l’utilisation des ...
2022System and method for transcoding spectral data with task-based optimization via symmetric non-negative matrix factorization
A computer-implemented method for reconstructing/recovering high-resolution visible light spectral data at a target resolution d, that comprises obtaining a configuration of a low- resolution multi-channel imaging sensor of resolution p, the configuration ...
2022Regularized Diffusion Adaptation via Conjugate Smoothing
The purpose of this article is to develop and study a decentralized strategy for Pareto optimization of an aggregate cost consisting of regularized risks. Each risk is modeled as the expectation of some loss function with unknown probability distribution, ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022Role of stochastic noise and generalization error in the time propagation of neural-network quantum states
Neural-network quantum states (NQS) have been shown to be a suitable variational ansatz to simulate out-of-equilibrium dynamics in two-dimensional systems using timedependent variational Monte Carlo (t-VMC). In particular, stable and accurate time propagat ...
SCIPOST FOUNDATION2022Associations between urinary biomarkers of oxidative stress and biomarkers of tobacco smoke exposure in smokers
Florian Frédéric Vincent Breider, Dominique Grandjean, Nicolas Sambiagio
Oxidative stress can contribute to the development of diseases, and may originate from exposures to toxicants commonly found in air pollution and cigarette smoke such as polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs). Yet, as ...
Elsevier2022Decentralized Semi-supervised Learning over Multitask Graphs
Ali H. Sayed, Roula Nassif, Elsa Rizk
In network semi-supervised learning problems, only a subset of the network nodes is able to access the data labeling. This paper formulates a decentralized optimization problem where agents have individual decision rules to estimate, subject to the conditi ...
IEEE2022