ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
The central issue in representing graphstructured data instances in learning algorithms is designing features which are invariant to permuting the numbering of the vertices. We pr...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
We propose a new algorithm for independent component and independent subspace analysis problems. This algorithm uses a contrast based on the Schweizer-Wolff measure of pairwise de...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
A broad class of boosting algorithms can be interpreted as performing coordinate-wise gradient descent to minimize some potential function of the margins of a data set. This class...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...