ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We present a novel approach for structure prediction that addresses the difficulty of obtaining labeled structures for training. We observe that structured output problems often h...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Local Coordinate Coding (LCC), introduced in (Yu et al., 2009), is a high dimensional nonlinear learning method that explicitly takes advantage of the geometric structure of the d...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...