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SIAMJO
2011
13 years 3 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
CORR
2008
Springer
156views Education» more  CORR 2008»
13 years 8 months ago
Artificial Immune Systems (AIS) - A New Paradigm for Heuristic Decision Making
Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annea...
Uwe Aickelin
ICDCS
2010
IEEE
14 years 15 days ago
Stochastic Steepest-Descent Optimization of Multiple-Objective Mobile Sensor Coverage
—We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the ...
Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Na...
SPAA
2004
ACM
14 years 2 months ago
Lower bounds for graph embeddings and combinatorial preconditioners
Given a general graph G, a fundamental problem is to find a spanning tree H that best approximates G by some measure. Often this measure is some combination of the congestion and...
Gary L. Miller, Peter C. Richter
MIDDLEWARE
2007
Springer
14 years 2 months ago
A piggybacking approach to reduce overhead in sensor network gossiping
Many wireless sensor network protocols are employing gossipbased message dissemination, where nodes probabilistically forward messages, to reduce message overhead. We are concerne...
Ercan Ucan, Nathanael Thompson, Indranil Gupta