Adaptive Kernel Value Caching for SVM Training

Adaptive Kernel Value Caching for SVM Training

10.1109/TNNLS.2019.2944562

Saved in:

Bibliographic Details
Main Authors:	Li, Qinbin, Wen, Zeyi, He, Bingsheng
Other Authors:	DEAN'S OFFICE (SCHOOL OF COMPUTING)
Format:	Article
Language:	English
Published:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 2022
Subjects:	Science & Technology Technology Computer Science, Artificial Intelligence Computer Science, Hardware & Architecture Computer Science, Theory & Methods Engineering, Electrical & Electronic Computer Science Engineering Training Support vector machines Kernel Libraries Learning systems Adaptive systems Runtime Caching efficiency kernel values support vector machines (SVMs)
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/215372
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	National University of Singapore
Language:	English

Similar Items

SVM compound kernel functions for vehicle target classification
by: Roxas, Edison A., et al.
Published: (2018)

Generating an SVM Kernel function using genetic algorithm
by: IMMER, BALDOS
Published: (2012)

Improved kernel methods for classification
by: DUAN KAIBO
Published: (2010)

Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms
by: Keerthi, S.S.
Published: (2014)

Discriminant analysis in pairwise kernel learning for SVM classification
by: Jiang, H., et al.
Published: (2014)

Incorporating prior-knowledge in support vector machines by kernel adaptation
by: Veillard, A., et al.
Published: (2013)

Text classification with kernels on the multinomial manifold
by: Zhang, D., et al.
Published: (2014)

Compactly supported basis functions as support vector kernels: Capturing feature interdependence in the embedding space
by: PETER WITTEK
Published: (2010)

Kernel methods for the incorporation of prior-knowledge into support vector machines
by: VEILLARD ANTOINE PAUL MITSUMASA
Published: (2013)

An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels
by: Lee, M.M.S., et al.
Published: (2014)

Large scale kernel methods for online AUC maximization
by: DING, Yi, et al.
Published: (2017)

Splice Site Prediction Using Support Vector Machines with a Bayes Kernel
by: ZHANG, Ya, et al.
Published: (2006)

Vehicle classification method using compound kernel functions
by: Roxas, Edison A., et al.
Published: (2018)

Question Classification using Support Vector Machines
by: Zhang, D., et al.
Published: (2013)

Essay question generator based on Bloom’s taxonomy for assessing automated essay scoring system
by: Contreras, Jennifer O., et al.
Published: (2021)

Semi-supervised SVM batch mode active learning for image retrieval
by: HOI, Steven, et al.
Published: (2008)

Robust regularized Kernel regression
by: ZHU, Jianke, et al.
Published: (2008)

Supervised and unsupervised machine learning for side-channel based Trojan detection
by: Jap, Dirmanto, et al.
Published: (2017)

Expediting the accuracy-improving process of SVMs for class imbalance learning
by: CAO, Bin, et al.
Published: (2021)

PRBF kernels: A framework for the incorporation of task-specific properties into support vector methods
by: Veillard, A., et al.
Published: (2013)

Convergence of a generalized SMO algorithm for SVM classifier design
by: Keerthi, S.S., et al.
Published: (2014)

A Multi-Scale Tikhonov Regularization Scheme for Implicit Surface Modeling
by: ZHU, Jianke, et al.
Published: (2007)

Double Updating Online Learning
by: ZHAO, Peilin, et al.
Published: (2011)

Predicting Student Carefulness within an Educational Game for Physics using Support Vector Machines
by: Banawan, Michelle P, et al.
Published: (2017)

Optimizing the cost function of histogram of oriented gradient-based INRIA dataset
by: Uy, Roger Luis, et al.
Published: (2014)

SMO-based system for identifying common lung conditions using histogram
by: De La Cruz, Ria Rodette G., et al.
Published: (2013)

A comparison of PCA, KPCA and ICA for dimensionality reduction in support vector machine
by: Cao, L.J., et al.
Published: (2014)

Feature selection via sensitivity analysis of SVM probabilistic outputs
by: Shen, K.-Q., et al.
Published: (2011)

A hybrid SOM-SVM approach for the zebrafish gene expression analysis
by: Wu, W., et al.
Published: (2013)

Prediction of relatedness in stack overflow: Deep learning vs. SVM: A reproducibility study
by: XU, Bowen, et al.
Published: (2018)

Learning the unified Kernel machines for classification
by: HOI, Steven C. H., et al.
Published: (2006)

Combining a global SVM and local nearest-neighbor classifiers driven by local discriminative boundaries
by: Xiong, W., et al.
Published: (2014)

Prediction of transporter family from protein sequence by support vector machine approach
by: Lin, H.H., et al.
Published: (2014)

Link Prediction in a Weighted Network Using Support Vector Machine
by: Co, Jan Miles, et al.
Published: (2016)

Combating Negative Transfer From Predictive Distribution Differences
by: Seah, Chun-Wei, et al.
Published: (2016)

Automatic identification and removal of artifacts in EEG using a probabilistic multi-class SVM approach with error correction
by: Shao, S.-Y., et al.
Published: (2014)

Forecasting of hydrologic time series with ridge regression in feature space
by: Yu, X., et al.
Published: (2014)

Using discrete probabilities with bhattacharyya measure for SVM-Based speaker verification
by: Lee, K.A., et al.
Published: (2013)

Biomedical image classification based on a cascade of an SVM with a reject option and subspace analysis
by: Lin, Dongyun, et al.
Published: (2020)

An HV-SVM classifier to infer TF-TF interactions using protein domains and GO annotations
by: Li, X.-L., et al.
Published: (2014)