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ICCV
2003
IEEE
16 years 1 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 3 months ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen
ACL
2012
13 years 2 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
QEST
2007
IEEE
15 years 6 months ago
Qualitative Logics and Equivalences for Probabilistic Systems
We investigate logics and equivalence relations that capture the qualitative behavior of Markov Decision Processes (MDPs). We present Qualitative Randomized Ctl (Qrctl): formulas o...
Luca de Alfaro, Krishnendu Chatterjee, Marco Faell...
NIPS
2004
15 years 1 months ago
Common-Frame Model for Object Recognition
A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appearance and pose are modeled probabilistically. ...
Pierre Moreels, Pietro Perona