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Distributed optimization of multi-class SVMs

Maximilian Alber, Julian Zimmert, Urun Dogan, Marius Kloft, Quan Zou
2017 PLoS ONE  
We develop distributed algorithms for two all-in-one SVM formulations (Lee et al. and Weston and Watkins) that parallelize the computation evenly over the number of classes.  ...  -rest SVMs can thus be trained on data involving a large number of classes.  ...  Note that beyond SVMs there is a large body of work on distributed multi-class [e.g., 41, 42] and multi-label learning algorithms [43] , which is outside of the scope of the present paper.  ... 
doi:10.1371/journal.pone.0178161 pmid:28570703 pmcid:PMC5453486 fatcat:n77hfxycvfhp3avx7umeyseliu

Piecewise Combination of Hyper-Sphere Support Vector Machine for Multi-Class Classification Problems

Shuang Liu
2019 International Journal of Performability Engineering  
Hyper-sphere Support vector machine (SVM) is a widely used machine learning method for multi-class classification problems such as image recognition, text classification, or handwriting recognition.  ...  In most cases, only one hyper-sphere optimization problem is computed to solve the problem. However, there are many complex applications with complicated data distributions.  ...  Acknowledgments This work is partially supported by the National Nature Science Foundation of Liaoning Province (No. 2015020099) and the National Natural Science Foundation (No. 71303031).  ... 
doi:10.23940/ijpe.19.06.p12.16111619 fatcat:ec5a6zpqmnfefjq4audyc37hpa

Comments on: Support vector machines maximizing geometric margins for multi-class classification

Shigeo Abe
2014 TOP - An Official Journal of the Spanish Society of Statistics and Operations Research  
Especially, because SVMs are basically binary classifiers, the extension to multi-class problems is not unique. Thus several multi-class SVMs have been developed.  ...  (The resulting separating hyperplane is called optimal separating hyperplane.) Much research has been conducted to improve the generalization ability of the SVMs.  ...  The optimal separating hyperplane is optimal when the distributions of class data are unknown. However, it is not optimal when they are known.  ... 
doi:10.1007/s11750-014-0339-7 fatcat:vbgygozs5bdbzfvwjbq2b4i2ha

A Novel Approach to Distributed Multi-Class SVM

Aruna Govada, Shree S S. Ranjani, Aditi Viswanathan, S.K. Sahay
2014 Transactions on Machine Learning and Artificial Intelligence  
Although substantial work has been done in developing distributed binary SVM algorithms and multi-class SVM algorithms individually, the field of multi-class distributed SVMs remains largely unexplored  ...  Rest) and out-performs them as the size of the dataset grows. This approach also classifies the data with higher accuracy than the traditional multi-class algorithms.  ...  Despite such extensive work on multi class SVMs as well as distributed binary SVMs, the arena of multi class distributed SVMs has remained largely unexplored.  ... 
doi:10.14738/tmlai.25.562 fatcat:7ysum45am5ahdahnehz5fvmjf4

Dendogram-based SVM for Multi-Class Classification

Khalid Benabdeslem, Younes Bennani
2006 Journal of Computing and Information Technology  
Therefore, DSVM method gives good results for multi-class problems by both, training an optimal number of SVMs and by rapidly classifying patterns in a descendant way by selecting an optimal set of SVMs  ...  The proposed method is compared to other multi-class SVM methods over several complex problems.  ...  In addition, we will present the time of training of each method and the number of trained SVMs for multi class SVM methods.  ... 
doi:10.2498/cit.2006.04.03 fatcat:fva7ru73x5dyppa7w2n7wte3um

Dendogram based SVM for multi-class classification

K. Benabdeslem, Y. Bennani
2006 28th International Conference on Information Technology Interfaces, 2006.  
Therefore, DSVM method gives good results for multi-class problems by both, training an optimal number of SVMs and by rapidly classifying patterns in a descendant way by selecting an optimal set of SVMs  ...  The proposed method is compared to other multi-class SVM methods over several complex problems.  ...  In addition, we will present the time of training of each method and the number of trained SVMs for multi class SVM methods.  ... 
doi:10.1109/iti.2006.1708473 fatcat:63b644wg2jhpjitqxdzdw3vmlm

Fault Diagnosis for Aero-engine Applying a New Multi-class Support Vector Algorithm

Qi-hua XU, Jun SHI
2006 Chinese Journal of Aeronautics  
The simulation results show that the designed H-SVMs can fast diagnose the multi-class single faults and combination faults for the gas path components of an aero-engine.  ...  Hierarchical Support Vector Machine (H-SVM) is faster in training and classification than other usual multi-class SVMs such as "1-V-R"and "1-V-1".  ...  Multi-class classification algorithm In terms of the optimal H-SVM construction, the corresponding binary SVMs are trained one after another with the training samples of sub-classes A and B.  ... 
doi:10.1016/s1000-9361(11)60342-7 fatcat:d22fnrcijjgutpele2q24rwmeq

A new maximal-margin spherical-structured multi-class support vector machine

Pei-Yi Hao, Jung-Hsien Chiang, Yen-Hsiu Lin
2007 Applied intelligence (Boston)  
SVMs provide the information of spherical center and radius, which characterize the probability distribution for each class more intuitive, and may be useful for dealing with class-imbalance problems.  ...  In addition, the center and radius of the class-specific hypersphere characterize the distribution of examples from that class, and may be useful for dealing with imbalance problems.  ...  One is all-together multi-class SVM that directly considers all classes in one optimization formulation [Weston, 1999; Crammer, 2000] , while the other is combined multi-class SVM that constructs several  ... 
doi:10.1007/s10489-007-0101-z fatcat:shqh2jjtw5a7zk73xbv3dlrwq4

The Application of Immune Guided Dtsvm in Fault Isolation

Yong Liu, Aiqiang Xu, Yu Liu
2011 Procedia Engineering  
Many multi-category SVMs are introduced in this paper briefly, and then an immune guided decision tree SVM (DTSVM) is presented which takes into account the fault occurring frequency.  ...  Support Vector Machine (SVM) is originally designed for linear binary pattern recognition. According to defect of common SVM, the Least square SVM is discussed to classify the small samples.  ...  Acknowledgements This work is supported by the Weapon Equipment Advanced Research Foundation of PLA (NO. 9140A25070208JB1402)  ... 
doi:10.1016/j.proeng.2011.08.618 fatcat:obch3dmodrb6ncxyyza4kwtg2q

Partial Linearization Based Optimization for Multi-class SVM [chapter]

Pritish Mohapatra, Puneet Kumar Dokania, C. V. Jawahar, M. Pawan Kumar
2016 Lecture Notes in Computer Science  
We propose a novel partial linearization based approach for optimizing the multi-class svm learning problem.  ...  Using the challenging computer vision problems of action classification, object recognition and gesture recognition, we demonstrate the efficacy of our approach on training multi-class svms with standard  ...  Preliminaries The Multi-class SVM Optimization Problem We provide a brief overview of the multi-class svm (mc-svm) optimization problem.  ... 
doi:10.1007/978-3-319-46454-1_51 fatcat:6i6zf5j35fc7riyf3ldxssv6ru

An Improved Skewness Decision Tree SVM Algorithm for the Classification of Steel Cord Conveyor Belt Defects

Qinghua Mao, Hongwei Ma, Xuhui Zhang, Guangming Zhang
2018 Applied Sciences  
In the proposed model, the classification order is determined by the sum of the Euclidean distances between multi-class sample centers and the parameters are optimized by the inertia weight Particle Swarm  ...  Skewness Decision Tree Support Vector Machine (SDTSVM) algorithm is widely known as a supervised learning model for multi-class classification problems.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app8122574 fatcat:szqysenusrcvxngyoz4iuyhjxa

Decision tree based Support Vector Machine for Intrusion Detection

Snehal A. Mulay, P. R. Devale, G.V. Garje
2010 2010 International Conference on Networking and Information Technology  
Support Vector Machines (SVM) are the classifiers which were originally designed for binary classification. The classification applications can solve multi-class problems.  ...  Decision-tree-based support vector machine which combines support vector machines and decision tree can be an effective way for solving multi-class problems in Intrusion Detection Systems ([OS).  ...  The obtained optimization problem is quadratic in (k -1) x I variables (where I denotes the number of the training patterns). The training of this multi-class SVM is usually very time-consuming.  ... 
doi:10.1109/icnit.2010.5508557 fatcat:xv6xpw3dw5ckjbmneckdcybsii

Support vector machine classification on a biased training set: Multi-jet background rejection at hadron colliders

Federico Sforza, Vittorio Lippi
2013 Nuclear Instruments and Methods in Physics Research Section A : Accelerators, Spectrometers, Detectors and Associated Equipment  
The procedure is applied to a real case of interest at hadron collider experiments: the reduction and the estimate of the multi-jet background in the W→ e ν plus jets data sample collected by the CDF experiment  ...  This is possible thanks to the feedback of a signal-background template fit performed on a validation sample and included both in the optimization process and in the input variable selection.  ...  Wolfe for the review of the manuscript.  ... 
doi:10.1016/j.nima.2013.04.046 fatcat:fnwhbvgpc5dp7nhifvvwcbou4u

Enhancing the Performance of an Intrusion Detection System Through Multi-Linear Dimensionality Reduction and Multi-Class SVM

Bukka Kumar, Mantena Raju, Bulusu Vardhan
2018 International Journal of Intelligent Engineering and Systems  
A Multi-class SVM (M-SVM) is used to detect whether the action is an attack or not. Here the Multi-class SVM is adopted to perform multi-attack classification in a layered fashion.  ...  In this work, a new dimensionality reduction technique combined with the Multi-class SVM (Support Vector Machine) is proposed for intrusion detection.  ...  The results obtained as, the value of rates obtained from Genetic algorithm is quite lesser than Multi Class SVM.  ... 
doi:10.22266/ijies2018.0228.19 fatcat:rjuwgynepjbbfmpvjwkg7mnd2y

Multi-label optimal margin distribution machine

Zhi-Hao Tan, Peng Tan, Yuan Jiang, Zhi-Hua Zhou
2019 Machine Learning  
Inspired by this idea, in this paper, we first introduce margin distribution to multi-label learning and propose multi-label Optimal margin Distribution Machine (mlODM), which optimizes the margin mean  ...  The pivotal idea is to maximize the minimum margin of label pairs, which is extended from SVM.  ...  Acknowledgements This research was supported by the National Key R&D Program of China (2018YFB1004300), NSFC (61673201), and the Collaborative Innovation Center of Novel Software Technology and Industrialization  ... 
doi:10.1007/s10994-019-05837-8 fatcat:okilchssg5efvceljvlqljz3ly
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