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» Algorithms for estimating relative importance in networks
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KDD
2003
ACM
217views Data Mining» more  KDD 2003»
14 years 5 months ago
Algorithms for estimating relative importance in networks
Large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis--examples include social networks, Web gra...
Scott White, Padhraic Smyth
QUESTA
2007
117views more  QUESTA 2007»
13 years 4 months ago
Estimating tail probabilities of heavy tailed distributions with asymptotically zero relative error
Efficient estimation of tail probabilities involving heavy tailed random variables is amongst the most challenging problems in Monte-Carlo simulation. In the last few years, appli...
Sandeep Juneja
AI
2007
Springer
13 years 11 months ago
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Changhe Yuan, Marek J. Druzdzel
ICRA
2009
IEEE
127views Robotics» more  ICRA 2009»
13 years 11 months ago
Relative bearing estimation from commodity radios
— Relative bearing between robots is important in applications like pursuit-evasion [11] and SLAM [7]. This is also true in in sensor networks, where the bearing of one sensor no...
Karthik Dantu, Prakhar Goyal, Gaurav S. Sukhatme
ETT
2002
142views Education» more  ETT 2002»
13 years 4 months ago
Adaptive state- dependent importance sampling simulation of markovian queueing networks
In this paper, a method is presented for the efficient estimation of rare-event (buffer overflow) probabilities in queueing networks using importance sampling. Unlike previously pr...
Pieter-Tjerk de Boer, Victor F. Nicola