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» Complexity of Inference in Graphical Models
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ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 10 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ICS
2010
Tsinghua U.
14 years 7 months ago
Cryptography by Cellular Automata or How Fast Can Complexity Emerge in Nature?
Computation in the physical world is restricted by the following spatial locality constraint: In a single unit of time, information can only travel a bounded distance in space. A ...
Benny Applebaum, Yuval Ishai, Eyal Kushilevitz
ICCV
2007
IEEE
15 years 2 days ago
Conditional State Space Models for Discriminative Motion Estimation
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
Minyoung Kim, Vladimir Pavlovic
CHI
2010
ACM
14 years 5 months ago
Understanding usability practices in complex domains
Although usability methods are widely used for evaluating conventional graphical user interfaces and websites, there is a growing concern that current approaches are inadequate fo...
Parmit K. Chilana, Jacob O. Wobbrock, Andrew J. Ko
ICCS
2005
Springer
14 years 3 months ago
A Comparative Study of Acceleration Techniques for Geometric Visualization
Abstract. Nowadays computer graphics hardware presents a series of characteristics, such as AGP memory, vertex cache, etc., that can be used for real-time rendering. The aim of thi...
Pascual Castelló, J. Francisco Ramos, Migue...