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» A Markov chain sequence generator for power macromodeling
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CVPR
2007
IEEE
15 years 12 months ago
Compositional Boosting for Computing Hierarchical Image Structures
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
Tianfu Wu, Gui-Song Xia, Song Chun Zhu
SFM
2007
Springer
15 years 4 months ago
Tackling Large State Spaces in Performance Modelling
Stochastic performance models provide a powerful way of capturing and analysing the behaviour of complex concurrent systems. Traditionally, performance measures for these models ar...
William J. Knottenbelt, Jeremy T. Bradley
ICASSP
2010
IEEE
14 years 10 months ago
Phone recognition using Restricted Boltzmann Machines
For decades, Hidden Markov Models (HMMs) have been the state-of-the-art technique for acoustic modeling despite their unrealistic independence assumptions and the very limited rep...
Abdel-rahman Mohamed, Geoffrey E. Hinton
ECCV
2008
Springer
16 years 2 months ago
Co-Recognition of Image Pairs by Data-Driven Monte Carlo Image Exploration
We introduce a new concept of co-recognition for object-level image matching between an arbitrary image pair. Our method augments putative local regionmatches to reliable object-...
Minsu Cho (Seoul National University), Young Min S...
AI
2006
Springer
14 years 10 months ago
Backward-chaining evolutionary algorithms
Starting from some simple observations on a popular selection method in Evolutionary Algorithms (EAs)--tournament selection--we highlight a previously-unknown source of inefficien...
Riccardo Poli, William B. Langdon