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» Approximating Average Parameters of Graphs
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AAAI
1998
13 years 9 months ago
Which Search Problems Are Random?
The typical difficulty of various NP-hard problems varies with simple parameters describing their structure. This behavior is largely independent of the search algorithm, but depe...
Tad Hogg
SODA
2010
ACM
261views Algorithms» more  SODA 2010»
14 years 5 months ago
Bidimensionality and Kernels
Bidimensionality theory appears to be a powerful framework in the development of meta-algorithmic techniques. It was introduced by Demaine et al. [J. ACM 2005 ] as a tool to obtai...
Fedor V. Fomin, Daniel Lokshtanov, Saket Saurabh, ...
NIPS
2007
13 years 9 months ago
Fixing Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations
We present a novel message passing algorithm for approximating the MAP problem in graphical models. The algorithm is similar in structure to max-product but unlike max-product it ...
Amir Globerson, Tommi Jaakkola
ECCV
2004
Springer
14 years 9 months ago
A Statistical Model for General Contextual Object Recognition
We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Peter Carbonetto, Nando de Freitas, Kobus Barnard
NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 11 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani