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» Complexity of Inference in Graphical Models
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ML
2006
ACM
131views Machine Learning» more  ML 2006»
15 years 2 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.
15 years 11 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
16 years 4 months 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
15 years 9 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
15 years 8 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...