226 search results - page 20 / 46 » How to learn a graph from smooth signals |
MICAI
2010
Springer
14 years 8 months ago
2010
Springer
The full deployment of service robots in daily activities will require the robot to adapt to the needs of non-expert users, particularly, to learn how to perform new tasks from “...
80
Voted
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
59
Voted
COLING
2008
14 years 11 months ago
2008
In this paper we describe an empirical study of human-human multi-tasking dialogues (MTD), where people perform multiple verbal tasks overlapped in time. We examined how conversan...
ICASSP
2010
IEEE
14 years 9 months ago
2010
IEEE
Amplitude demodulation is an ill-posed problem and so it is natural to treat it from a Bayesian viewpoint, inferring the most likely carrier and envelope under probabilistic const...
90
Voted
WSDM
2009
ACM
15 years 4 months ago
2009
ACM
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...