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PAMI
2012
13 years 9 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
ICML
2005
IEEE
16 years 7 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
184
Voted
PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
16 years 1 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
158
Voted
ILP
2000
Springer
15 years 10 months ago
Bayesian Logic Programs
First-order probabilistic models are recognized as efficient frameworks to represent several realworld problems: they combine the expressive power of first-order logic, which serv...
Kristian Kersting, Luc De Raedt
WSC
2007
15 years 8 months ago
Simulating air traffic blockage due to convective weather conditions
A Monte Carlo methodology is proposed for simulating air traffic blockage patterns under the impact of convective weather. The simulation utilizes probabilistic convective weather...
Liling Ren, Dawei Chang, Senay Solak, John-Paul Cl...