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CVPR
2012
IEEE
11 years 11 months ago
Augmenting deformable part models with irregular-shaped object patches
The performance of part-based object detectors generally degrades for highly flexible objects. The limited topological structure of models and pre-specified part shapes are two ...
Roozbeh Mottaghi
NIPS
1998
13 years 10 months ago
An Entropic Estimator for Structure Discovery
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Matthew Brand
JMLR
2010
165views more  JMLR 2010»
13 years 3 months ago
Learning with Blocks: Composite Likelihood and Contrastive Divergence
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
ICML
2004
IEEE
14 years 9 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh
RECOMB
2006
Springer
14 years 9 months ago
Markov Additive Chains and Applications to Fragment Statistics for Peptide Mass Fingerprinting
Abstract. Peptide mass fingerprinting is a technique to identify a protein from its fragment masses obtained by mass spectrometry after enzymatic digestion. Recently, much attentio...
Hans-Michael Kaltenbach, Sebastian Böcker, Sv...