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» Approximate Learning of Dynamic Models
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AAAI
2007
15 years 7 months ago
Nonmyopic Informative Path Planning in Spatio-Temporal Models
In many sensing applications we must continuously gather information to provide a good estimate of the state of the environment at every point in time. A robot may tour an environ...
Alexandra Meliou, Andreas Krause, Carlos Guestrin,...
ACSD
2010
IEEE
219views Hardware» more  ACSD 2010»
15 years 3 months ago
The Model Checking View to Clock Gating and Operand Isolation
Abstract--Clock gating and operand isolation are two techniques to reduce the power consumption in state-of-the-art hardware designs. Both approaches basically follow a two-step pr...
Jens Brandt, Klaus Schneider, Sumit Ahuja, Sandeep...
ICPR
2008
IEEE
16 years 6 months ago
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
AMEC
2003
Springer
15 years 10 months ago
Improving Learning Performance by Applying Economic Knowledge
Digital information economies require information goods producers to learn how to position themselves within a potentially vast product space. Further, the topography of this spac...
Christopher H. Brooks, Robert S. Gazzale, Jeffrey ...
UAI
2003
15 years 6 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller