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AAAI
2006
13 years 5 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
13 years 10 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 8 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 8 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
13 years 10 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...