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ICML
2005
IEEE
14 years 7 months ago
Naive Bayes models for probability estimation
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Daniel Lowd, Pedro Domingos
CVPR
2012
IEEE
11 years 8 months ago
From Pictorial Structures to deformable structures
Pictorial Structures (PS) define a probabilistic model of 2D articulated objects in images. Typical PS models assume an object can be represented by a set of rigid parts connecte...
Silvia Zuffi, Oren Freifeld, Michael J. Black
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 2 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
CVPR
2011
IEEE
13 years 2 months ago
Particle Filter with State Permutations for Solving Image Jigsaw Puzzles
We deal with an image jigsaw puzzle problem, which is defined as reconstructing an image from a set of square and non-overlapping image patches. It is known that a general instan...
Xingwei Yang, Nagesh Adluru, LonginJan Latecki
ICPR
2004
IEEE
14 years 7 months ago
A Hybrid Face Recognition Method using Markov Random Fields
We propose a hybrid face recognition method that combines holistic and feature analysis-based approaches using a Markov random field (MRF) model. The face images are divided into ...
Dimitris N. Metaxas, Rui Huang, Vladimir Pavlovic