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NIPS
2000
13 years 11 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
DAGM
2009
Springer
13 years 11 months ago
Depth Imaging by Combining Time-of-Flight and On-Demand Stereo
In this paper we present a framework for computing depth images at interactive rates. Our approach is based on combining time-of-flight (TOF) range data with stereo vision. We use ...
Uwe Hahne, Marc Alexa
ADHOC
2008
122views more  ADHOC 2008»
13 years 10 months ago
Balancing computation and communication costs: The case for hybrid execution in sensor networks
Virtual machines (VM) are promising as system software in sensor networks. A major impediment to their widespread acceptance is their performance overhead. Compiling VM bytecode to...
Joel Koshy, Ingwar Wirjawan, Raju Pandey, Yann Ram...
ENTCS
2006
127views more  ENTCS 2006»
13 years 10 months ago
Tool support for MOLA
The paper describes the MOLA Tool, which supports the model transformation language MOLA. MOLA Tool consists of two parts: MOLA definition environment and MOLA execution environme...
Audris Kalnins, Edgars Celms, Agris Sostaks
FGCS
2000
93views more  FGCS 2000»
13 years 9 months ago
Sharing objects in a distributed, single address space environment
With reference to an object type defining the two basic operations, read and write, we present solutions to the object sharing problem, classified according to the migration and/o...
Gianluca Dini, Lanfranco Lopriore