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NIPS
1998
15 years 5 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
CCE
2006
15 years 4 months ago
Parameter estimation in continuous-time dynamic models using principal differential analysis
Principal differential analysis (PDA) is an alternative parameter estimation technique for differential equation models in which basis functions (e.g., B-splines) are fitted to dy...
A. A. Poyton, M. S. Varziri, K. B. McAuley, P. J. ...
ICSOC
2010
Springer
15 years 2 months ago
BPMN Modelling of Services with Dynamically Reconfigurable Transactions
We promote the use of transactional attributes for modelling business processes in the service-oriented scenario. Transactional attributes have been introduced in Enterprise JavaBe...
Laura Bocchi, Roberto Guanciale, Daniele Strollo, ...
MICRO
2010
IEEE
119views Hardware» more  MICRO 2010»
15 years 2 months ago
A Predictive Model for Dynamic Microarchitectural Adaptivity Control
Abstract--Adaptive microarchitectures are a promising solution for designing high-performance, power-efficient microprocessors. They offer the ability to tailor computational resou...
Christophe Dubach, Timothy M. Jones, Edwin V. Boni...
DSD
2009
IEEE
93views Hardware» more  DSD 2009»
15 years 2 months ago
Transactions Sequence Tracking by means of Dynamic Binary Instrumentation of TLM Models
Several traditional VHDL fault injection mechanisms like mutants or saboteurs have been adapted to SystemC model descriptions. The main drawback of these approaches is the necessi...
Antonio da Silva, Sebastian Sanchez