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PODS
2008
ACM
123views Database» more  PODS 2008»
16 years 4 months ago
Evaluating rank joins with optimal cost
In the rank join problem, we are given a set of relations and a scoring function, and the goal is to return the join results with the top K scores. It is often the case in practic...
Karl Schnaitter, Neoklis Polyzotis
ALDT
2009
Springer
142views Algorithms» more  ALDT 2009»
15 years 11 months ago
Finding Best k Policies
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Peng Dai, Judy Goldsmith
GECCO
2005
Springer
197views Optimization» more  GECCO 2005»
15 years 10 months ago
Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics
In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. ...
Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Sha...
DIALM
2004
ACM
113views Algorithms» more  DIALM 2004»
15 years 10 months ago
Gathering correlated data in sensor networks
In this paper, we consider energy-efficient gathering of correlated data in sensor networks. We focus on single-input coding strategies in order to aggregate correlated data. For ...
Pascal von Rickenbach, Roger Wattenhofer
ICASSP
2010
IEEE
15 years 4 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa