ICML
2009
IEEE
13 years 9 months ago
2009
IEEE
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
ICML
2009
IEEE
13 years 9 months ago
2009
IEEE
We often seek to identify co-occurring hidden features in a set of observations. The Indian Buffet Process (IBP) provides a nonparametric prior on the features present in each obs...
ICML
2009
IEEE
13 years 9 months ago
2009
IEEE
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
Empirical evidence suggests that hashing is an effective strategy for dimensionality reduction and practical nonparametric estimation. In this paper we provide exponential tail bo...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
The maximum margin clustering approach is a recently proposed extension of the concept of support vector machines to the clustering problem. Briefly stated, it aims at finding a...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing ...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ra...