ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
This paper suggests a method for multiclass learning with many classes by simultaneously learning shared characteristics common to the classes, and predictors for the classes in t...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
A geometric and non parametric procedure for testing if two nite set of points are linearly separable is proposed. The Linear Separability Test is equivalent to a test that deter...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Regularized Kernel Discriminant Analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. The performance of RKDA depends on the selection o...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The ...
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...