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» Evaluating algorithms that learn from data streams
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SIGMOD
2003
ACM
161views Database» more  SIGMOD 2003»
16 years 20 days ago
Approximate Join Processing Over Data Streams
We consider the problem of approximating sliding window joins over data streams in a data stream processing system with limited resources. In our model, we deal with resource cons...
Abhinandan Das, Johannes Gehrke, Mirek Riedewald
KDD
1998
ACM
84views Data Mining» more  KDD 1998»
15 years 4 months ago
Towards the Personalization of Algorithms Evaluation in Data Mining
Like model selectionin statistics,the choiceof appropriate Data Mining Algorithms (DM-Algorithms) is a very importanttask in the processof KnowledgeDiscovery.Due to this fact it i...
Gholamreza Nakhaeizadeh, Alexander Schnabl
TNN
2008
178views more  TNN 2008»
15 years 12 days ago
IMORL: Incremental Multiple-Object Recognition and Localization
This paper proposes an incremental multiple-object recognition and localization (IMORL) method. The objective of IMORL is to adaptively learn multiple interesting objects in an ima...
Haibo He, Sheng Chen
ICRA
2008
IEEE
169views Robotics» more  ICRA 2008»
15 years 7 months ago
Sparse incremental learning for interactive robot control policy estimation
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
Daniel H. Grollman, Odest Chadwicke Jenkins
147
Voted
DAGSTUHL
2007
15 years 2 months ago
An XML Framework for Integrating Continuous Queries, Composite Event Detection, and Database Condition Monitoring for Multiple D
Abstract Current, data-driven applications have become more dynamic in nature, with the need to respond to events generated from distributed sources or to react to information extr...
Susan Darling Urban, Suzanne W. Dietrich, Yi Chen