Results 71 to 80 of about 3,187,155 (299)
A Sharper Generalization Bound for Divide-and-Conquer Ridge Regression
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 We study the distributed machine learning problem where the n feature-response pairs are partitioned among m machines uniformly at random. The goal is to approximately solve an empirical risk minimization (ERM) problem with the minimum amount of communication.
openaire +3 more sources
Some theoretical results for generalized ridge regression estimators [PDF]
Journal of Econometrics, 1984 We examine some interpretations and theoretical properties of the ridge regression estimators. As such we (i) interpret the GRR estimator as an OLS one based on transformed explanatory variables; (ii) compare the GRR and OLS estimators using the confidence regions; (iii) prove the optimality of the OLS estimator for estimating the signs of the ...
Fourgeaud Claude +2 more
openaire +2 more sources
Advanced Science, EarlyView.A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley +1 more source
Advanced Science, EarlyView.This study established a high‐quality organoid biobank derived from 68 tumor sites across 50 Chinese patients, elucidated the drug sensitivity‐based molecular subtyping in breast cancer, and revealed a novel mechanism of drug resistance mediated by the FAK‐ACSL1 pathway.
Hao Xu +10 more
wiley +1 more source
Employing Ridge Regression Procedure to Remedy the Multicollinearity Problem
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2017 In this paper we introduce many different Methods of ridge regression to solve multicollinearity problem in linear regression model. These Methods include two types of ordinary ridge regression (ORR1), (ORR2) according to the choice of ridge ...
Hazim M. Gorgees, Bushra A. Ali
doaj
Multi-site joint correction method for real-time flood forecasting errors
Shui kexue jinzhanReal-time correction is an essential technique for enhancing the accuracy of river flood forecasts. To overcome the challenges of terminal correction methods in describing spatial error propagation and the coefficient instability inherent in traditional ...
Qi LIU +6 more
doaj +1 more source
Advanced Science, EarlyView.An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park +3 more
wiley +1 more source
Advanced Science, EarlyView.Furrow tillage resolves the conventional‐vs.‐no‐tillage trade‐off by simultaneously cutting CO2 efflux to 2.0–3.0 g C m−2 d−1 and unlocking high nutrient availability for the rice rhizosphere. This scalable agronomic solution strengthens soil health, enhances plant physiology, reshapes microbial metabolism, and shifts paddy systems toward a net ...
Arnab Majumdar +10 more
wiley +1 more source
Performance evaluation of different regression models: application in a breast cancer patient data
Scientific ReportsThis paper provides a comprehensive analysis of linear regression models, focusing on addressing multicollinearity challenges in breast cancer patient data.
Mona Mahmoud Abo El Nasr +2 more
doaj +1 more source
Combining Quadratic Penalization and Variable Selection via Forward Boosting [PDF]
, 2011 Quadratic penalties can be used to incorporate external knowledge about the association structure among regressors. Unfortunately, they do not enforce single estimated regression coefficients to equal zero.
Tutz, Gerhard, Ulbricht, Jan
core +1 more source