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» Incremental Recompilation of Knowledge
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ML
2008
ACM
14 years 9 months ago
Incremental exemplar learning schemes for classification on embedded devices
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Ankur Jain, Daniel Nikovski
ADVIS
2004
Springer
15 years 3 months ago
Incremental Association Rule Mining Using Materialized Data Mining Views
Data mining is an interactive and iterative process. Users issue series of similar queries until they receive satisfying results, yet currently available data mining systems do not...
Mikolaj Morzy, Tadeusz Morzy, Zbyszko Króli...
ICML
2006
IEEE
15 years 10 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
101
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HIPEAC
2009
Springer
15 years 4 months ago
Collective Optimization
Abstract. Iterative compilation is an efficient approach to optimize programs on rapidly evolving hardware, but it is still only scarcely used in practice due to a necessity to gat...
Grigori Fursin, Olivier Temam
KDD
2002
ACM
146views Data Mining» more  KDD 2002»
15 years 10 months ago
Closed Set Mining of Biological Data
We present a closed set data mining paradigm which is particularly e ective for uncovering the kind of deterministic, causal dependencies that characterize much of basic science. ...
John L. Pfaltz, Christopher M. Taylor