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TC
2008
15 years 6 months ago
The Convergence-Guaranteed Random Walk and Its Applications in Peer-to-Peer Networks
Network structure construction and global state maintenance are expensive in large-scale, dynamic peer-to-peer (p2p) networks. With inherent topology independence and low state mai...
Ming Zhong, Kai Shen, Joel I. Seiferas
JAIR
2002
182views more  JAIR 2002»
15 years 6 months ago
An Analysis of Phase Transition in NK Landscapes
In this paper, we analyze the decision version of the NK landscape model from the perspective of threshold phenomena and phase transitions under two random distributions, the unif...
Yong Gao, Joseph C. Culberson
ECCV
2010
Springer
15 years 6 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
ICIP
2010
IEEE
15 years 4 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
ASPDAC
2009
ACM
115views Hardware» more  ASPDAC 2009»
16 years 1 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