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PR
2007
189views more  PR 2007»
14 years 9 months ago
Information cut for clustering using a gradient descent approach
We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between p...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
CORR
2010
Springer
107views Education» more  CORR 2010»
14 years 8 months ago
Distributed Detection over Time Varying Networks: Large Deviations Analysis
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...
Dragana Bajovic, Dusan Jakovetic, João Xavi...
INFOCOM
2010
IEEE
14 years 8 months ago
Design and Analysis of a Robust Pipelined Memory System
Abstract—Many network processing applications require wirespeed access to large data structures or a large amount of flowlevel data, but the capacity of SRAMs is woefully inadeq...
Hao Wang, Haiquan (Chuck) Zhao, Bill Lin, Jun Xu
RSA
2010
98views more  RSA 2010»
14 years 8 months ago
Merging percolation on Zd and classical random graphs: Phase transition
: We study a random graph model which is a superposition of bond percolation on Zd with parameter p, and a classical random graph G(n, c/n). We show that this model, being a homoge...
Tatyana S. Turova, Thomas Vallier
TKDE
2010
224views more  TKDE 2010»
14 years 8 months ago
Probabilistic Topic Models for Learning Terminological Ontologies
—Probabilistic topic models were originally developed and utilised for document modeling and topic extraction in Information Retrieval. In this paper we describe a new approach f...
Wang Wei, Payam M. Barnaghi, Andrzej Bargiela