ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The conditional distribution of a discrete variable y, given another discrete variable x, is often specified by assigning one multinomial distribution to each state of x. The cost...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We investigate the empirical applicability of several bounds (a number of which are new) on the true error rate of learned classifiers which hold whenever the examples are chosen ...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
We introduce flexible algorithms that can automatically learn mappings from images to actions by interacting with their environment. They work by introducing an image classifier i...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
This paper presents a learning theoretical analysis of correlation clustering (Bansal et al., 2002). In particular, we give bounds on the error with which correlation clustering r...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
This paper presents a Support Vector Method for optimizing multivariate nonlinear performance measures like the F1score. Taking a multivariate prediction approach, we give an algo...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
AdaBoost.OC has shown to be an effective method in boosting "weak" binary classifiers for multi-class learning. It employs the Error Correcting Output Code (ECOC) method...