Results 31 to 40 of about 4,818,434 (320)

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples [PDF]

open access: yesAAAI Conference on Artificial Intelligence, 2017
Recent studies have highlighted the vulnerability of deep neural networks (DNNs) to adversarial examples — a visually indistinguishable adversarial image can easily be crafted to cause a well-trained model to misclassify.
Pin-Yu Chen   +4 more
semanticscholar   +1 more source

Detection of functional and structural brain alterations in female schizophrenia using elastic net logistic regression. [PDF]

open access: yesBrain Imaging Behav, 2022
Neuroimaging technique is a powerful tool to characterize the abnormality of brain networks in schizophrenia. However, the neurophysiological substrate of schizophrenia is still unclear.
Wu Y   +9 more
europepmc   +2 more sources

Prediction of the critical temperature of a superconductor by using the WOA/MARS, Ridge, Lasso and Elastic-net machine learning techniques

open access: yesNeural computing & applications (Print), 2021
This study builds a predictive model capable of estimating the critical temperature of a superconductor from experimentally determined physico-chemical properties of the material (input variables): features extracted from the thermal conductivity, atomic
P. J. García–Nieto   +2 more
semanticscholar   +1 more source

Merging Clinical and EEG Biomarkers in an Elastic-Net Regression for Disorder of Consciousness Prognosis Prediction

open access: yesIEEE transactions on neural systems and rehabilitation engineering, 2022
Patients with Disorder of Consciousness (DoC) entering Intensive Rehabilitation Units after a severe Acquired Brain Injury have a highly variable evolution of the state of consciousness which is a complex aspect to predict.
Piergiuseppe Liuzzi   +12 more
semanticscholar   +1 more source

Fast learning rate of multiple kernel learning: Trade-off between sparsity and smoothness [PDF]

open access: yes, 2013
We investigate the learning rate of multiple kernel learning (MKL) with $\ell_1$ and elastic-net regularizations. The elastic-net regularization is a composition of an $\ell_1$-regularizer for inducing the sparsity and an $\ell_2$-regularizer for ...
Sugiyama, Masashi, Suzuki, Taiji
core   +2 more sources

High Dimensional QSAR Study of Mild Steel Corrosion Inhibition in acidic medium by Furan Derivatives

open access: yesInternational Journal of Electrochemical Science, 2015
The inhibition of mild steel corrosion in 1 M HCl by 17 furan derivatives was investigated experimentally using potentiodynamic polarization measurements. The furan derivatives inhibit the mild steel corrosion. The experimental inhibition efficiency (IE)
Abdo M. Al-Fakih   +5 more
doaj   +1 more source

Pyglmnet : Python implementation of elastic-net regularized generalized linear models [PDF]

open access: yes, 2020
Graceful handling of small Hessian term in coordinate descent solver that led to exploding update term Ensure full compatibility of GLM class with scikit ...
Achakulvisut, Titipat   +21 more
core   +1 more source

Elastic Net Constraints for Shape Matching [PDF]

open access: yes2013 IEEE International Conference on Computer Vision, 2013
We consider a parametrized relaxation of the widely adopted quadratic assignment problem (QAP) formulation for minimum distortion correspondence between deformable shapes. In order to control the accuracy/sparsity trade-off we introduce a weighting parameter on the combination of two existing relaxations, namely spectral and game-theoretic.
Rodola, Emanuele   +4 more
openaire   +1 more source

Prediction of internal egg quality characteristics and variable selection using regularization methods: ridge, LASSO and elastic net [PDF]

open access: yesArchives Animal Breeding, 2018
This study was conducted to determine the inner quality characteristics of eggs using external egg quality characteristics. The variables were selected in order to obtain the simplest model using ridge, LASSO and elastic net regularization methods ...
M. N. Çiftsüren, S. Akkol
doaj   +1 more source

On the adaptive elastic-net with a diverging number of parameters [PDF]

open access: yes, 2009
We consider the problem of model selection and estimation in situations where the number of parameters diverges with the sample size. When the dimension is high, an ideal method should have the oracle property [J. Amer. Statist. Assoc.
Zhang, Hao Helen, Zou, Hui
core   +2 more sources

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