Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
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TLDR
Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.Abstract:
LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.read more
Citations
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Journal ArticleDOI
Fuzzy Broad Learning System: A Novel Neuro-Fuzzy Model for Regression and Classification
Shuangg Feng,C. L. Philip Chen +1 more
TL;DR: A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by merging the Takagi–Sugeno (TS) fuzzy system into BLS, and the results indicate that fuzzy BLS outperforms other models involved.
Journal ArticleDOI
What Makes a Photograph Memorable
TL;DR: It is shown that memorability is an intrinsic and stable property of an image that is shared across different viewers, and remains stable across delays, and is a first attempt to quantify this useful property of images.
Journal ArticleDOI
A study on reduced support vector machines
Kuan-Ming Lin,Chih-Jen Lin +1 more
TL;DR: It is shown that the RSVM formulation is already in a form of linear SVM and four RSVM implementations are discussed, which indicates that in general the test accuracy of RSVM are a little lower than that of the standard SVM.
Proceedings Article
Speedup Matrix Completion with Side Information: Application to Multi-Label Learning
Miao Xu,Rong Jin,Zhi-Hua Zhou +2 more
TL;DR: It is shown that, under appropriate conditions, with the assistance of side information matrices, the number of observed entries needed for a perfect recovery of matrix M can be dramatically reduced to O(ln n).
Proceedings ArticleDOI
Secure unlocking of mobile touch screen devices by simple gestures: you can see it but you can not do it
TL;DR: Unlike existing authentication schemes for touch screen devices, which use what user inputs as the authentication secret, GEAT authenticates users mainly based on how they input, using distinguishing features such as finger velocity, device acceleration, and stroke time.
References
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Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Proceedings ArticleDOI
A training algorithm for optimal margin classifiers
TL;DR: A training algorithm that maximizes the margin between the training patterns and the decision boundary is presented, applicable to a wide variety of the classification functions, including Perceptrons, polynomials, and Radial Basis Functions.
A Practical Guide to Support Vector Classication
TL;DR: A simple procedure is proposed, which usually gives reasonable results and is suitable for beginners who are not familiar with SVM.
Journal ArticleDOI
A comparison of methods for multiclass support vector machines
Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.