719 search results - page 4 / 144 » Discriminative learning for differing training and test dist... |
CVPR
2005
IEEE
14 years 7 months ago
2005
IEEE
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
TSP
2010
12 years 12 months ago
2010
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
NIPS
2008
13 years 6 months ago
2008
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
INTERSPEECH
2010
13 years 3 days ago
2010
We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial fac...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...