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KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 6 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
AI
2000
Springer
13 years 6 months ago
Stochastic dynamic programming with factored representations
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Craig Boutilier, Richard Dearden, Moisés Go...
ASMTA
2008
Springer
167views Mathematics» more  ASMTA 2008»
13 years 8 months ago
Perfect Simulation of Stochastic Automata Networks
The solution of continuous and discrete-time Markovian models is still challenging mainly when we model large complex systems, for example, to obtain performance indexes of paralle...
Paulo Fernandes, Jean-Marc Vincent, Thais Webber
JSAC
2010
107views more  JSAC 2010»
13 years 4 months ago
Online learning in autonomic multi-hop wireless networks for transmitting mission-critical applications
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Hsien-Po Shiang, Mihaela van der Schaar