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ICML
2010
IEEE
14 years 19 days ago
Mixed Membership Matrix Factorization
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
Lester W. Mackey, David Weiss, Michael I. Jordan
ICML
2010
IEEE
14 years 19 days ago
COFFIN: A Computational Framework for Linear SVMs
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...
Sören Sonnenburg, Vojtech Franc
ICML
2010
IEEE
14 years 19 days ago
Structured Output Learning with Indirect Supervision
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...
Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Da...
ICML
2010
IEEE
14 years 19 days ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
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...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
ICML
2010
IEEE
14 years 19 days ago
Two-Stage Learning Kernel Algorithms
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
ICML
2010
IEEE
14 years 19 days ago
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
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...
Seyoung Kim, Eric P. Xing
ICML
2010
IEEE
14 years 19 days ago
Non-Local Contrastive Objectives
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...
David Vickrey, Cliff Chiung-Yu Lin, Daphne Koller
ICML
2010
IEEE
14 years 19 days ago
Robust Formulations for Handling Uncertainty in Kernel Matrices
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 ...
Sahely Bhadra, Sourangshu Bhattacharya, Chiranjib ...
ICML
2010
IEEE
14 years 19 days ago
Improved Local Coordinate Coding using Local Tangents
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...
Kai Yu, Tong Zhang
ICML
2010
IEEE
14 years 19 days ago
Finding Planted Partitions in Nearly Linear Time using Arrested Spectral Clustering
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...
Nader H. Bshouty, Philip M. Long