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IJON
2007
184views more  IJON 2007»
15 years 6 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
ECCV
2006
Springer
16 years 8 months ago
Machine Learning for High-Speed Corner Detection
Abstract Where feature points are used in real-time frame-rate applications, a high-speed feature detector is necessary. Feature detectors such as SIFT (DoG), Harris and SUSAN are ...
Edward Rosten, Tom Drummond
ISPASS
2009
IEEE
16 years 1 months ago
Machine learning based online performance prediction for runtime parallelization and task scheduling
—With the emerging many-core paradigm, parallel programming must extend beyond its traditional realm of scientific applications. Converting existing sequential applications as w...
Jiangtian Li, Xiaosong Ma, Karan Singh, Martin Sch...
AEI
1999
134views more  AEI 1999»
15 years 6 months ago
Automatic design synthesis with artificial intelligence techniques
Design synthesis represents a highly complex task in the field of industrial design. The main difficulty in automating it is the definition of the design and performance spaces, i...
Francisco J. Vico, Francisco J. Veredas, Jos&eacut...
ICMLA
2010
15 years 4 months ago
Heuristic Method for Discriminative Structure Learning of Markov Logic Networks
Markov Logic Networks (MLNs) combine Markov Networks and first-order logic by attaching weights to firstorder formulas and viewing them as templates for features of Markov Networks...
Quang-Thang Dinh, Matthieu Exbrayat, Christel Vrai...