Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
A re-weighting strategy for improving margins
Artificial Intelligence
On the Learnability and Design of Output Codes for Multiclass Problems
COLT '00 Proceedings of the Thirteenth Annual Conference on Computational Learning Theory
On the algorithmic implementation of multiclass kernel-based vector machines
The Journal of Machine Learning Research
Discriminant Pattern Recognition Using Transformation-Invariant Neurons
Neural Computation
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We extend multiclass SVM to multiple prototypes per class. For this framework, we give a compact constrained quadratic problem and we suggest an efficient algorithm for its optimization that guarantees a local minimum of the objective function. An annealed process is also proposed that helps to escape from local minima. Finally, we report experiments where the performance obtained using linear models is almost comparable to that obtained by state-of-art kernel-based methods but with a significant reduction (of one or two orders) in response time.