313 search results - page 31 / 63 » Hierarchical sampling for active learning |
MM
2005
ACM
14 years 4 months ago
2005
ACM
The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays...
CORR
2010
Springer
13 years 11 months ago
2010
Springer
In many networks, vertices have hidden attributes that are correlated with the network's topology. For instance, in social networks, people are more likely to be friends if t...
ICML
2010
IEEE
13 years 12 months ago
2010
IEEE
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
NIPS
2008
14 years 9 days ago
2008
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
UAI
2004
14 years 8 days ago
2004
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...