Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
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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Proceedings ArticleDOI
Detecting depression from facial actions and vocal prosody
Jeffrey F. Cohn,Tomas Simon Kruez,Iain Matthews,Ying Yang,Minh Hoai Nguyen,Margara Tejera Padilla,Feng Zhou,Fernando De la Torre +7 more
TL;DR: The findings suggest the feasibility of automatic detection of depression, raise new issues in automated facial image analysis and machine learning, and have exciting implications for clinical theory and practice.
Proceedings ArticleDOI
Multi-label learning by exploiting label dependency
Min-Ling Zhang,Kun Zhang +1 more
TL;DR: This paper proposes to use a Bayesian network structure to efficiently encode the conditional dependencies of the labels as well as the feature set, with the featureSet as the common parent of all labels.
Journal ArticleDOI
Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease
Siqi Liu,Sidong Liu,Weidong Cai,Hangyu Che,Sonia Pujol,Ron Kikinis,Dagan Feng,Michael J. Fulham,Adni +8 more
TL;DR: This framework uses a zero-masking strategy for data fusion to extract complementary information from multiple data modalities to aid the diagnosis of AD and has the potential to require less labeled data.
Journal ArticleDOI
Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks
TL;DR: It is demonstrated that D3Net can be used to efficiently extract salient object masks from real scenes, enabling effective background-changing application with a speed of 65 frames/s on a single GPU.
Journal ArticleDOI
Transductive Multi-View Zero-Shot Learning
TL;DR: A novel heterogeneous multi-view hypergraph label propagation method is formulated for zero-shot learning in the transductive embedding space that rectifies the projection shift between the auxiliary and target domains, exploits the complementarity of multiple semantic representations, and significantly outperforms existing methods for both zero- shot and N-shot recognition.
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.
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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.