Sciweavers

1407 search results - page 4 / 282
» Learning Abstract Scheduling Models
Sort
View
CI
2002
92views more  CI 2002»
13 years 9 months ago
Model Selection in an Information Economy: Choosing What to Learn
As online markets for the exchange of goods and services become more common, the study of markets composed at least in part of autonomous agents has taken on increasing importance...
Christopher H. Brooks, Robert S. Gazzale, Rajarshi...
PDPTA
2004
13 years 11 months ago
Hierarchical Scheduling for State-based Services
Abstract-- Service descriptions based on type hiernd abstract service states ruling the availability of operations permit more secure service combinations in distributed systems de...
Jens Bruhn, Sven Kaffille, Guido Wirtz
MVA
2002
195views Computer Vision» more  MVA 2002»
13 years 9 months ago
Improved Adaptive Mixture Learning for Robust Video Background Modeling
2 Related Works Gaussian mixtures are often used for data modeling in many real-time applications such as video background modeling and speaker direction tracking. The real-time a...
Dar-Shyang Lee
ICML
1999
IEEE
14 years 10 months ago
Abstracting from Robot Sensor Data using Hidden Markov Models
ing from Robot Sensor Data using Hidden Markov Models Laura Firoiu, Paul Cohen Computer Science Department, LGRC University of Massachusetts at Amherst, Box 34610 Amherst, MA 01003...
Laura Firoiu, Paul R. Cohen
ISORC
2008
IEEE
14 years 4 months ago
Compositional Feasibility Analysis of Conditional Real-Time Task Models
Conditional real-time task models, which are generalizations of periodic, sporadic, and multi-frame tasks, represent real world applications more accurately. These models can be c...
Madhukar Anand, Arvind Easwaran, Sebastian Fischme...