With the increase of the training set’s size, the efficiency of support vector machine (SVM) classifier will be confined. To solve such a problem, a novel preextracting method f...
Deqiang Han, Chongzhao Han, Yi Yang, Yu Liu, Wenta...
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
A key problem in playing strategy games is learning how to allocate resources effectively. This can be a difficult task for machine learning when the connections between actions a...
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...