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CEC
2010
IEEE
13 years 8 months ago
Iterated local search vs. hyper-heuristics: Towards general-purpose search algorithms
An important challenge within hyper-heuristic research is to design search methodologies that work well, not only across different instances of the same problem, but also across di...
Edmund K. Burke, Timothy Curtois, Matthew R. Hyde,...
PPOPP
2005
ACM
14 years 29 days ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 11 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
DAWAK
2004
Springer
14 years 24 days ago
Algorithms for Discovery of Frequent Superset, Rather than Frequent Subset
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...
Zhung-Xun Liao, Man-Kwan Shan
IPPS
2002
IEEE
14 years 10 days ago
FARM: A Feedback-Based Adaptive Resource Management for Autonomous Hot-Spot Convergence System
Abstract— In this paper, we present a novel and comprehensive resource management solution for the autonomous hot-spot convergence system (AHSCS) that uses sensor web. This solut...
S. Swaminathan, G. Manimaran