1407 search results - page 67 / 282 » Learning Abstract Scheduling Models |
ECCV
2002
Springer
15 years 11 months ago
2002
Springer
Abstract. This paper considers the dynamic tree (DT) model, first introduced in [1]. A dynamic tree specifies a prior over structures of trees, each of which is a forest of one or ...
RECOMB
2004
Springer
15 years 10 months ago
2004
Springer
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
PKDD
2010
Springer
14 years 8 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...
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CLOR
2006
15 years 1 months ago
2006
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
ECCV
2008
Springer
15 years 12 months ago
2008
Springer
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...