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» A Bayesian Approach to Tackling Hard Computational Problems
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CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
16 years 6 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
SEMWEB
2010
Springer
14 years 9 months ago
Evolution of DL - Lite Knowledge Bases
Abstract. We study the problem of evolution for Knowledge Bases (KBs) expressed in Description Logics (DLs) of the DL-Lite family. DL-Lite is at the basis of OWL 2 QL, one of the t...
Diego Calvanese, Evgeny Kharlamov, Werner Nutt, Dm...
TNN
2008
124views more  TNN 2008»
14 years 11 months ago
Just-in-Time Adaptive Classifiers - Part II: Designing the Classifier
Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolu...
Cesare Alippi, Manuel Roveri
AAAI
2000
15 years 17 days ago
Recognizing End-User Transactions in Performance Management
Providing good quality of service (e.g., low response times) in distributed computer systems requires measuring enduser perceptions of performance. Unfortunately, such measures ar...
Joseph L. Hellerstein, T. S. Jayram, Irina Rish
EWSN
2004
Springer
15 years 10 months ago
Context-Aware Sensors
Wireless sensor networks typically consist of a large number of sensor nodes embedded in a physical space. Such sensors are low-power devices that are primarily used for monitoring...
Eiman Elnahrawy, Badri Nath