4591 search results - page 275 / 919 » Learning from Dyadic Data |
158
Voted
ACCV
2010
Springer
14 years 12 months ago
2010
Springer
Abstract. We present a novel approach to detect and classify rare behaviours which are visually subtle and occur sparsely in the presence of overwhelming typical behaviours. We tre...
117
click to vote
ICML
2009
IEEE
16 years 5 months ago
2009
IEEE
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
152
click to vote
ICIAP
2005
ACM
16 years 5 months ago
2005
ACM
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
134
click to vote
BIBM
2007
IEEE
15 years 11 months ago
2007
IEEE
Discovering human disease-causing genes (disease genes in short) is one of the most challenging problems in bioinformatics and biomedicine, as most diseases are related in some wa...
151
click to vote
PKDD
2010
Springer
15 years 3 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...