Proximity control in bundle methods for convex
Mathematical Programming: Series A and B
The nature of statistical learning theory
The nature of statistical learning theory
Making large-scale support vector machine learning practical
Advances in kernel methods
Semi-supervised support vector machines
Proceedings of the 1998 conference on Advances in neural information processing systems II
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Proximal support vector machine classifiers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Minimizing Nonconvex Nonsmooth Functions via Cutting Planes and Proximity Control
SIAM Journal on Optimization
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Semi-Supervised Learning on Riemannian Manifolds
Machine Learning
Optimization Techniques for Semi-Supervised Support Vector Machines
The Journal of Machine Learning Research
Cuts3vm: a fast semi-supervised svm algorithm
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Non-smoothness in classification problems
Optimization Methods & Software - THE JOINT EUROPT-OMS CONFERENCE ON OPTIMIZATION, 4-7 JULY, 2007, PRAGUE, CZECH REPUBLIC, PART I
A bi-fuzzy progressive transductive support vector machine(BFPTSVM) algorithm
Expert Systems with Applications: An International Journal
A novel transductive learning algorithm based on multi-agent-system
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Semi-supervised Bayesian ARTMAP
Applied Intelligence
Expert Systems with Applications: An International Journal
Margin maximization in spherical separation
Computational Optimization and Applications
A class of semi-supervised support vector machines by DC programming
Advances in Data Analysis and Classification
An illumination problem: optimal apex and optimal orientation for a cone of light
Journal of Global Optimization
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We apply nonsmooth optimization techniques to classification problems, with particular reference to the TSVM (Transductive Support Vector Machine) approach, where the considered decision function is nonconvex and nondifferentiable and then difficult to minimize. We present some numerical results obtained by running the proposed method on some standard test problems drawn from the binary classification literature.