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IJON
2008
118views more  IJON 2008»
13 years 9 months ago
Incremental extreme learning machine with fully complex hidden nodes
Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden nodes, IEEE Trans. Neural Networks 17(4) (2006) 879
Guang-Bin Huang, Ming-Bin Li, Lei Chen, Chee Kheon...
IJCV
2006
161views more  IJCV 2006»
13 years 9 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert
EAAI
2006
123views more  EAAI 2006»
13 years 9 months ago
Imitation learning with spiking neural networks and real-world devices
This article is about a new approach in robotic learning systems. It provides a method to use a real-world device that operates in real-time, controlled through a simulated recurr...
Harald Burgsteiner
ASPDAC
2009
ACM
115views Hardware» more  ASPDAC 2009»
14 years 4 months ago
Incremental and on-demand random walk for iterative power distribution network analysis
— Power distribution networks (PDNs) are designed and analyzed iteratively. Random walk is among the most efficient methods for PDN analysis. We develop in this paper an increme...
Yiyu Shi, Wei Yao, Jinjun Xiong, Lei He
INFOCOM
2010
IEEE
13 years 8 months ago
Reliability in Layered Networks with Random Link Failures
—We consider network reliability in layered networks where the lower layer experiences random link failures. In layered networks, each failure at the lower layer may lead to mult...
Kayi Lee, Hyang-Won Lee, Eytan Modiano