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AAAI
2006
15 years 2 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
WWW
2005
ACM
16 years 2 months ago
On the feasibility of low-rank approximation for personalized PageRank
Personalized PageRank expresses backlink-based page quality around user-selected pages in a similar way to PageRank over the entire Web. Algorithms for computing personalized Page...
András A. Benczúr, Károly Csa...
DATAMINE
2006
89views more  DATAMINE 2006»
15 years 1 months ago
Scalable Clustering Algorithms with Balancing Constraints
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
Arindam Banerjee, Joydeep Ghosh
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 7 months ago
Using pair approximations to predict takeover dynamics in spatially structured populations
The topological properties of a network directly impact the flow of information through a system. For example, in natural populations, the network of inter-individual contacts aff...
Joshua L. Payne, Margaret J. Eppstein
ISLPED
2007
ACM
123views Hardware» more  ISLPED 2007»
15 years 3 months ago
Approximation algorithms for power minimization of earliest deadline first and rate monotonic schedules
We address power minimization of earliest deadline first and ratemonotonic schedules by voltage and frequency scaling. We prove that the problems are NP-hard, and present (1+ ) f...
Sushu Zhang, Karam S. Chatha, Goran Konjevod