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GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 8 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
SIGMOD
2009
ACM
137views Database» more  SIGMOD 2009»
14 years 7 months ago
Advances in flash memory SSD technology for enterprise database applications
The past few decades have witnessed a chronic and widening imbalance among processor bandwidth, disk capacity, and access speed of disk. According to Amdhal's law, the perfor...
Sang-Won Lee, Bongki Moon, Chanik Park
COLT
2007
Springer
14 years 1 months ago
Resource-Bounded Information Gathering for Correlation Clustering
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
Pallika Kanani, Andrew McCallum
ASC
2011
13 years 2 months ago
Autonomic fault-handling and refurbishment using throughput-driven assessment
A new paradigm for online EH regeneration using Genetic Algorithms (GAs) called Competitive Runtime Reconfiguration (CRR) is developed where performance is assessed based upon a b...
Ronald F. DeMara, Kening Zhang, Carthik A. Sharma
MLDM
2005
Springer
14 years 1 months ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...