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AAAI
2006
13 years 9 months ago
Embedding Heterogeneous Data Using Statistical Models
Embedding algorithms are a method for revealing low dimensional structure in complex data. Most embedding algorithms are designed to handle objects of a single type for which pair...
Amir Globerson, Gal Chechik, Fernando Pereira, Naf...
CODES
2007
IEEE
14 years 1 months ago
Event-based re-training of statistical contention models for heterogeneous multiprocessors
Embedded single-chip heterogeneous multiprocessor (SCHM) systems experience frequent system events such as task preemption, power-saving voltage/frequency scaling, or arrival of n...
Alex Bobrek, JoAnn M. Paul, Donald E. Thomas
ISSS
2000
IEEE
191views Hardware» more  ISSS 2000»
13 years 11 months ago
Conditional Scheduling for Embedded Systems using Genetic List Scheduling
One important part of a HW/SW codesign system is the scheduler which is needed in order to determine if a given HW/SW partitioning is suitable for a given application. In this pap...
Martin Grajcar
COOPIS
2004
IEEE
13 years 11 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar
CIKM
2005
Springer
14 years 1 months ago
Establishing value mappings using statistical models and user feedback
In this paper, we present a “value mapping” algorithm that does not rely on syntactic similarity or semantic interpretation of the values. The algorithm first constructs a st...
Jaewoo Kang, Tae Sik Han, Dongwon Lee, Prasenjit M...