Results 111 to 120 of about 326,273 (311)

Twin support vector quantile regression

Expert Systems with Applications
We propose a twin support vector quantile regression (TSVQR) to capture the heterogeneous and asymmetric information in modern data. Using a quantile parameter, TSVQR effectively depicts the heterogeneous distribution information with respect to all portions of data points.
Yafen Ye, Zhihu Xu, Jinhua Zhang, Weijie Chen 0001, Yuanhai Shao 0001   +4 more
openaire   +2 more sources

Ultrasmall High‐Entropy Materials: Nanoscale Effects, Synthesis, and Mechanistic Insights

Advanced Functional Materials, EarlyView.
This review article focuses on sub‐10 nm high‐entropy materials that combine nanoscale design with complex compositions for next‐generation applications. ABSTRACT Ultrasmall high‐entropy nanomaterials (USHENMs, <10 nm) merge multicomponent chemistry with size‐dependent effects, forming a distinct class of materials with unprecedented properties.
Yueyue He, Wenbo Wang, Simon Schweidler, Yanjiao Ma, Ben Breitung, Torsten Brezesinski   +5 more
wiley   +1 more source

Consistency and robustness of kernel based regression [PDF]

We investigate properties of kernel based regression (KBR) methods which are inspired by the convex risk minimization method of support vector machines.
Christmann, Andreas, Steinwart, Ingo
core  

Thermally Pre‐Formed Reconfigurable Resistive Random‐Access Memory Crossbar Arrays: A Dual‐Mode Platform for Robust Physically Unclonable Functions and In‐Memory Computing

Advanced Functional Materials, EarlyView.
A reconfigurable RRAM platform utilizing thermally pre‐formed filaments (TPFs) is developed to realize robust hardware security. By exploiting the thermodynamic stochasticity of TPFs, exceptionally reliable physically unclonable functions (PUFs) are achieved.
Seongbin Kwon, Taewon Lee, Dohyeong Kim, Sungmin Hwang, Sungjoon Kim   +4 more
wiley   +1 more source

Blind equalization algorithm based on complex support vector regression

Tongxin xuebao, 2019
A new blind equalization algorithm for complex valued signals was proposed based on the framework of complex support vector regression(CSVR).In the proposed algorithm,the error function of multi-modulus algorithm (MMA) was substituted into CSVR to ...
Ling YANG, Liang CHEN, Bin ZHAO, Guolong ZHANG, Yuan LI   +4 more
doaj   +2 more sources

A working set algorithm for support vector regression problems

Journal of Numerical Analysis and Approximation Theory
Due to its dual quadratic structure and the existence of complex structural constraints, support vector regression (SVR) is still a computationally intensive operation.
Saida Azib, Belkacem Brahmi
doaj   +1 more source

Development of a Three‐Axis Planar Hall Magnetoresistance Sensor Using a Superparamagnetic Nanoparticle‐Based Flux Guide

Advanced Functional Materials, EarlyView.
A printed superparamagnetic nanoparticle‐based flux guide enables the realization of a hysteresis‐free three‐axis magnetic sensor. This innovative architecture efficiently redirects out‐of‐plane fields to planar sensing elements, facilitating simultaneous vector detection without complex reset protocols.
Changyeop Jeon, Mijin Kim, Keonmok Kim, Byeonghwa Lim, Bibhutibhusan Nayak, Youngdo Jung, Bo‐Yeon Lee, Taehyeong Jeon, Jinwoo Kim, Sunjong Oh, CheolGi Kim   +10 more
wiley   +1 more source

The Default Risk of Firms Examined with Smooth Support Vector Machines [PDF]

In the era of Basel II a powerful tool for bankruptcy prognosis is vital for banks. The tool must be precise but also easily adaptable to the bank's objections regarding the relation of false acceptances (Type I error) and false rejections (Type II error)
Yuh-Jye Lee, Wolfgang Härdle, Dorothea Schäfer, Yi-Ren Yeh   +3 more
core  

Flash Assembloids: A Rapid Biofabrication of a Platform for Modeling Early Glioblastoma Invasion at the Glioblastoma–Brain Organoid Interfaces

Advanced Healthcare Materials, EarlyView.
This study presents a bioengineered assembloid (ASM) system combining glioblastoma (GBM) cells in oxidized alginate (OA) microgels with dorsal organoids (DOs). This model simulates brain tumor‐host interactions, revealing enhanced GBM invasion, altered gene expression, and aggressive infiltration patterns, demonstrating ASM as a valuable platform for ...
Chao Liang, Henry Robert Howard, Shihui Chen, Won‐Young Choi, Summer Cao, Arthur Chien, Kevin Zou, Michael Kassiou, Fabien Delerue, Ho Sang Jung, Yeonju Park, Young Mee Jung, Yong‐Dae Kwon, Karrie M. Kiang, Gilberto Ka‐Kit Leung, Ryohichi Sugimura, Ann‐Na Cho, Sang Jin Lee   +17 more
wiley   +1 more source

Support Vector Machines in R

Being among the most popular and efficient classification and regression methods currently available, implementations of support vector machines exist in almost every popular programming language.
Kurt Hornik, David Meyer, Alexandros Karatzoglou   +2 more
core