Results 61 to 70 of about 43,564 (255)

Waveguide Photoactuators: Materials, Fabrication, and Applications

open access: yesAdvanced Robotics Research, EarlyView.
Waveguide photoactuators convert guided light into mechanical motion. Their tethered‐flexible design enables minimally invasive surgery and confined‐space robotics. This review aims to guide materials selection, device design, and system integration, accelerating the transition of waveguide photoactuators from laboratory prototypes to versatile ...
Minjie Xi   +4 more
wiley   +1 more source

ELM Ridge Regression Boosting

open access: yesCoRR, 2023
We discuss a boosting approach for the Ridge Regression (RR) method, with applications to the Extreme Learning Machine (ELM), and we show that the proposed method significantly improves the classification performance and robustness of ELMs.
openaire   +2 more sources

Modified Ridge Regression With Cook’s Distance for Semiparametric Regression Models

open access: yesJournal of Mathematics
Multicollinearity and influential cases in semiparametric regression models lead to biased and unreliable estimates distorting leverage and residual patterns.
Najeeb Mahmood Khan   +3 more
doaj   +1 more source

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

open access: yesAdvanced 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

Efficiency of conformalized ridge regression

open access: yesCoRR, 2014
Conformal prediction is a method of producing prediction sets that can be applied on top of a wide range of prediction algorithms. The method has a guaranteed coverage probability under the standard IID assumption regardless of whether the assumptions (often considerably more restrictive) of the underlying algorithm are satisfied.
Evgeny Burnaev, Vladimir Vovk
openaire   +3 more sources

Random Design Analysis of Ridge Regression [PDF]

open access: yesFoundations of Computational Mathematics, 2014
This work gives a simultaneous analysis of both the ordinary least squares estimator and the ridge regression estimator in the random design setting under mild assumptions on the covariate/response distributions. In particular, the analysis provides sharp results on the ``out-of-sample'' prediction error, as opposed to the ``in-sample'' (fixed design ...
Hsu, Daniel   +2 more
openaire   +4 more sources

Weighted Ridge Regression: Combining Ridge and Robust Regression Methods [PDF]

open access: yes, 1973
This paper gives the formulas for and derivation of ridge regression methods when there are weights associated with each observation. A Bayesian motivation is used and various choices of k are discussed. A suggestion is made as to how to combine ridge regression with robust regression methods.
openaire   +2 more sources

Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling

open access: yesAdvanced 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

Bayesian Analyses of Ridge Regression Prooblems

open access: yesIbn 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  

Semi-Supervised Ridge Regression with Adaptive Graph-Based Label Propagation

open access: yesApplied Sciences, 2018
In order to overcome the drawbacks of the ridge regression and label propagation algorithms, we propose a new semi-supervised classification method named semi-supervised ridge regression with adaptive graph-based label propagation (SSRR-AGLP).
Yugen Yi   +6 more
doaj   +1 more source

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