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CVPR
2007
IEEE
16 years 1 months ago
Learning Conditional Random Fields for Stereo
State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose heuristic restrictions or priors on disparities, for e...
Daniel Scharstein, Chris Pal
FUIN
2008
108views more  FUIN 2008»
14 years 10 months ago
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
Wannes Meert, Jan Struyf, Hendrik Blockeel
110
Voted
AI
2007
Springer
14 years 11 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang

Publication
350views
15 years 11 months ago
Probabilistic Parameter Selection for Learning Scene Structure from Video
We present an online learning approach for robustly combining unreliable observations from a pedestrian detector to estimate the rough 3D scene geometry from video sequences of a...
Michael D. Breitenstein, Eric Sommerlade, Bastian ...
PODS
2007
ACM
196views Database» more  PODS 2007»
15 years 11 months ago
On the complexity of managing probabilistic XML data
In [3], we introduced a framework for querying and updating probabilistic information over unordered labeled trees, the probabilistic tree model. The data model is based on trees ...
Pierre Senellart, Serge Abiteboul