ICML
2003
IEEE
15 years 15 days 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
15 years 15 days 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
15 years 15 days 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
15 years 15 days 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
15 years 15 days 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
15 years 15 days 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
15 years 15 days ago
2003
IEEE
ICML
2003
IEEE
15 years 15 days ago
2003
IEEE
ICML
2004
IEEE
15 years 15 days 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
15 years 15 days 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...