Sciweavers

74 search results - page 7 / 15
» Learning in Dynamic Environments: Decision Trees for Data St...
Sort
View
ICML
2000
IEEE
15 years 10 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
ICAS
2006
IEEE
139views Robotics» more  ICAS 2006»
15 years 3 months ago
Predicting Resource Demand in Dynamic Utility Computing Environments
— We target the problem of predicting resource usage in situations where the modeling data is scarce, non-stationary, or expensive to obtain. This scenario occurs frequently in c...
Artur Andrzejak, Sven Graupner, Stefan Plantikow
ISVC
2010
Springer
14 years 8 months ago
On Supervised Human Activity Analysis for Structured Environments
We consider the problem of developing an automated visual solution for detecting human activities within industrial environments. This has been performed using an overhead view. Th...
Banafshe Arbab-Zavar, Imed Bouchrika, John N. Cart...
SIGMOD
2007
ACM
188views Database» more  SIGMOD 2007»
15 years 10 months ago
Keyword search on relational data streams
Increasing monitoring of transactions, environmental parameters, homeland security, RFID chips and interactions of online users rapidly establishes new data sources and applicatio...
Alexander Markowetz, Yin Yang, Dimitris Papadias
JMLR
2010
130views more  JMLR 2010»
14 years 4 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...