Results 91 to 100 of about 33,950 (290)

Coupling Nanostructured Plasmon–Strain Microwave Waveguide to Spin Defects in Hexagonal Boron Nitride for High‐Sensitivity Quantum Sensors

Advanced Materials, EarlyView.
Coupling of spin‐active VB−$V_B^ - $ defects in hBN with alumina‐coated gold plasmonic nanoresonators (PNRs), integrated into a microwave‐efficient waveguide, constitutes a plasmon‐strain architecture that enhances their photoluminescence and spin contrast. This platform enables a tenfold quantum yield improvement and achieves a DC magnetic sensitivity
Naveed Hussain, Sumukh Vaidya, Saakshi Dikshit, Shahriar Esmaeili, Paul Schmalenberg, Hayate Yamano, Katsunori Danno, Biswajit Sahoo, Shougo Higashi, Ercan M. Dede, Tongcang Li, Debasish Banerjee, Songtao Wu   +12 more
wiley   +1 more source

Multi-task Regression using Minimal Penalties [PDF]

, 2011
In this paper we study the kernel multiple ridge regression framework, which we refer to as multi-task regression, using penalization techniques. The theoretical analysis of this problem shows that the key element appearing for an optimal calibration is ...
Arlot, Sylvain, Bach, Francis, Solnon, Matthieu   +2 more
core   +6 more sources

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, Alouini, Mohamed-Slim, Elkhalil, Khalil, Kammoun, Abla, Zhang, Xiangliang   +4 more
core   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

A Bootstrap Lasso + Partial Ridge Method to Construct Confidence Intervals for Parameters in High-dimensional Sparse Linear Models

, 2020
Constructing confidence intervals for the coefficients of high-dimensional sparse linear models remains a challenge, mainly because of the complicated limiting distributions of the widely used estimators, such as the lasso.
Li, Jingyi Jessica, Liu, Hanzhong, Xu, Xin   +2 more
core   +1 more source

Generalized Mode and Ridge Estimation

, 2014
The generalized density is a product of a density function and a weight function. For example, the average local brightness of an astronomical image is the probability of finding a galaxy times the mean brightness of the galaxy. We propose a method for studying the geometric structure of generalized densities.
Chen, Yen-Chi, Genovese, Christopher R., Wasserman, Larry   +2 more
openaire   +2 more sources

Anomalous Spin‐Optical Helical Effect in Ti‐Based Kagome Metal

Advanced Materials, EarlyView.
The kagome lattice hosts diverse correlated quantum states, including elusive loop currents. We report spin‐handedness selective signals in CsTi3Bi5, termed the anomalous spin‐optical helical effect, surpassing conventional spin responses. Arising from light helicity coupled to spin‐orbital correlations, this effect provides a sensitive, indirect probe
Federico Mazzola, Wojciech Brzezicki, Chiara Bigi, Armando Consiglio, Luciano Jacopo D'Onofrio, Maria Teresa Mercaldo, Adam Kłosiński, François Bertran, Patrick Le Fèvre, Oliver J. Clark, Mark T. Edmonds, Manuel Tuniz, Alessandro De Vita, Vincent Polewczyk, Jeppe B. Jacobsen, Henrik Jacobsen, Jill A. Miwa, Justin W. Wells, Anupam Jana, Ivana Vobornik, Jun Fujii, Niccolo Mignani, Narges Tarakameh Samani, Alberto Crepaldi, Giorgio Sangiovanni, Anshu Kataria, Tommaso Morresi, Samuele Sanna, Pietro Bonfá, Brenden R. Ortiz, Ganesh Pokharel, Stephen D. Wilson, Domenico Di Sante, Carmine Ortix, Mario Cuoco   +34 more
wiley   +1 more source

A comparative study of the performance of new ridge estimators for multicollinearity: Insights from simulation and real data application

AIP Advances
This paper addresses the challenge of multicollinearity in regression models, a condition that inflates the standard errors of coefficients, leading to unreliable estimates and wider confidence intervals.
Nadeem Akhtar, Muteb Faraj Alharthi
doaj   +1 more source

Estimation in regret-regression using quadratic inference functions with ridge estimator. [PDF]

PLoS One, 2022
Abdul Jalil NR, Mohamed NA, Mohamad Yunus R.   +2 more
europepmc   +1 more source

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates [PDF]

, 2014
We establish optimal convergence rates for a decomposition-based scalable approach to kernel ridge regression. The method is simple to describe: it randomly partitions a dataset of size N into m subsets of equal size, computes an independent kernel ridge
Duchi, John C., Wainwright, Martin J., Zhang, Yuchen   +2 more
core