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» The Time-Triggered Model of Computation
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KDD
2005
ACM
160views Data Mining» more  KDD 2005»
16 years 7 months ago
Optimizing time series discretization for knowledge discovery
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
Alfred Ultsch, Fabian Mörchen
209
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KDD
2003
ACM
162views Data Mining» more  KDD 2003»
16 years 7 months ago
Improving spatial locality of programs via data mining
In most computer systems, page fault rate is currently minimized by generic page replacement algorithms which try to model the temporal locality inherent in programs. In this pape...
Karlton Sequeira, Mohammed Javeed Zaki, Boleslaw K...
KDD
2002
ACM
160views Data Mining» more  KDD 2002»
16 years 7 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...
VLSID
2008
IEEE
128views VLSI» more  VLSID 2008»
16 years 7 months ago
Addressing the Challenges of Synchronization/Communication and Debugging Support in Hardware/Software Cosimulation
With increasing adoption of Electronic System Level (ESL) tools, effective design and validation time has reduced to a considerable extent. Cosimulation is found to be a principal...
Banit Agrawal, Timothy Sherwood, Chulho Shin, Simo...
VLSID
2006
IEEE
156views VLSI» more  VLSID 2006»
16 years 7 months ago
SEAT-LA: A Soft Error Analysis Tool for Combinational Logic
Radiation induced soft errors in combinational logic is expected to become as important as directly induced errors on state elements. Consequently, it has become important to deve...
Jungsub Kim, Mary Jane Irwin, Narayanan Vijaykrish...
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