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UAI
2001
15 years 2 months ago
2001
We consider the task of aggregating beliefs of several experts. We assume that these beliefs are represented as probability distributions. We argue that the evaluation of any aggr...
103
Voted
ICML
2002
IEEE
16 years 1 months ago
2002
IEEE
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
106
Voted
ICML
1998
IEEE
16 years 1 months ago
1998
IEEE
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...
127
Voted
ICCV
2005
IEEE
16 years 3 months ago
2005
IEEE
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
112
Voted
COLT
2010
Springer
14 years 11 months ago
2010
Springer
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...