ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
In many real world applications, active selection of training examples can significantly reduce the number of labelled training examples to learn a classification function. Differ...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
This paper is concerned with the question of how to online combine an ensemble of active learners so as to expedite the learning progress during a pool-based active learning sessi...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
We address the problem of learning distance metrics using side-information in the form of groups of "similar" points. We propose to use the RCA algorithm, which is a sim...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Receiver Operating Characteristic (ROC) curves provide a powerful tool for visualizing and comparing classification results. Regression Error Characteristic (REC) curves generaliz...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective pro...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...