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- Kernel Adaptive Filtering: A Comprehensive Introduction638
Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces and addresses the principal bottleneck of kernel adaptive filterstheir growing structure.
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- Kernel Affine Projection Algorithms193
KAPA inherits the simplicity and online nature of KLMS while reducing its gradient noise, boosting performance and provides a unifying model for several neural network techniques, including kernel least-mean-square algorithms, kernel adaline, sliding-window kernel recursive-least squares, and regularization networks.
- Canonical correlation analysis networks for two-view image recognition123
A canonical correlation analysis network (CCANet) is presented to address image classification, in which images are represented by two-view features, and the experimental results demonstrate that the CCANet algorithm is more effective than PCANet, RandNet-1 andRandNet-2.
- On a PCA-based lung motion model122
The goal of this work is to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling and propose a new method to derive the entire lung motion using a single internal marker based on the PCA model.
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- Hessian Regularized Support Vector Machines for Mobile Image Annotation on the Cloud108
A scheme for image annotation on the cloud is presented, which transmits mobile images compressed by Hamming compressed sensing to the cloud and conducts semantic annotation through a novel Hessian regularized support vector machine on thecloud.
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- Multiview dimension reduction via Hessian multiset canonical correlations100
HesMCC is presented, which takes the advantage of Hessian and provides superior extrapolating capability and finally leverage the performance of TCCA, KMUDA, MCCA and LapMCC for multiview dimension reduction.
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- Detecting structural damage under unknown seismic excitation by deep convolutional neural network with wavelet-based transmissibility data86
A new approach is proposed for detecting structural damage subject to unknown seismic excitation based on a convolutional neural network with wavelet-based transmissibility of structural response data using the ability in subtle information acquisition of wavelet transform.
- Multiview Hessian regularized logistic regression for action recognition78
This paper carefully conduct extensive experiments on the unstructured social activity attribute (USAA) dataset and the experimental results demonstrate the effectiveness of the proposed multiview Hessian regularized logistic regression for human action recognition.
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- A coordinated optimization framework for long-term complementary operation of a large-scale hydro-photovoltaic hybrid system: Nonlinear modeling, multi-objective optimization and robust decision-making63
A coordinated optimization framework for the long-term complementary operation of large-scale hydro-PV hybrid systems is established that simultaneously optimizes the economic benefit and operational safety of the hybrid system and a novel robust decision-making model is developed to evaluate, rank and select the Pareto optimal solutions.
- A multi-objective risk management model for real-time flood control optimal operation of a parallel reservoir system63
The results show that the developed multi-objective risk management model can provide operation schedules that satisfy flood control objectives and simultaneously minimize the overall risks.
- HesGCN: Hessian graph convolutional networks for semi-supervised classification62
HesGCN can learn more efficient data features by fusing the original feature information with its structure information based on Hessian, and gets a more efficient convolution layer rule by optimizing the one-order spectral graph Hessian convolutions.
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- Multiview Cauchy Estimator Feature Embedding for Depth and Inertial Sensor-Based Human Action Recognition61
A new unsupervised feature fusion method termed multiview Cauchy estimator feature embedding (MCEFE) for human action recognition is proposed, which integrates the encoded complementary information in multiple views to find the unified data representation and the projection matrices.
- HSAE: A Hessian regularized sparse auto-encoders60
This paper incorporates both Hessian regularization and sparsity constraints into auto-encoders and proposed HSAE outperforms the related baseline algorithms and efficiently extracts the hidden structure in the data by using sparsity constraint.
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- Semi-supervised classification by graph p-Laplacian convolutional networks55
This paper exploits the manifold structure information of data by the graph p -Laplacian matrix and proposes the graph p -Laplacian convolutional networks (GpLCN), which can extract more abundant sample features and improves the classification performance utilizing graph p -Laplacian to preserve the rich intrinsic data manifold structure information.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-16. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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