Results 101 to 110 of about 3,667,438 (313)
IEEE Photonics Journal, 2020 We put forward and demonstrate a angle-of-arrival (AOA) based visible-light-positioning (VLP) system using quadrant-solar-cell (QSC) and third-order ridge regression machine learning (RRML) to improve the positioning accuracy.
C. Hong +9 more
semanticscholar +1 more source
Advanced Robotics Research, EarlyView.This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka +3 more
wiley +1 more source
Bayesian Analyses of Ridge Regression Prooblems
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2017 A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new ...
H. M. Gorgees
doaj
The Matrix Ridge Approximation: Algorithms and Applications [PDF]
, 2013 We are concerned with an approximation problem for a symmetric positive semidefinite matrix due to motivation from a class of nonlinear machine learning methods. We discuss an approximation approach that we call {matrix ridge approximation}.
Zhang, Zhihua
core
Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling
Advanced Robotics Research, EarlyView.This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou +4 more
wiley +1 more source
Takeuchi's Information Criteria as a form of Regularization
, 2018 Takeuchi's Information Criteria (TIC) is a linearization of maximum likelihood estimator bias which shrinks the model parameters towards the maximum entropy distribution, even when the model is mis-specified.
Dixon, Matthew, Ward, Tyler
core +1 more source
Advanced Science, EarlyView.We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich +2 more
wiley +1 more source
Risk Convergence of Centered Kernel Ridge Regression with Large Dimensional Data
, 2019 This paper carries out a large dimensional analysis of a variation of kernel ridge regression that we call \emph{centered kernel ridge regression} (CKRR), also known in the literature as kernel ridge regression with offset.
Al-Naffouri, Tareq +4 more
core +1 more source
Advanced Science, EarlyView.This study reveals that maternal antibiotic exposure prior to conception disrupts intergenerational gut microbial succession. By enhancing maternal‐offspring microbial transmission, altering microbial developmental trajectories and increasing selective pressures during community assembly, these disturbances lead to persistent gut mucosal immaturity and
Yuzhu Chen +8 more
wiley +1 more source
Ridge regression revisited [PDF]
We argue in this paper that general ridge (GR) regression implies no major complication compared with simple ridge regression. We introduce a generalization of an explicit GR estimator derived by Hemmerle and by Teekens and de Boer and show that this ...
Boer, P.M.C. de, Hafner, C.M.
core +1 more source