1071 search results - page 106 / 215 » Using Cell-DEVS for Modeling Complex Cell Spaces |
128
Voted
ESSMAC
2003
Springer
15 years 8 months ago
2003
Springer
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
137
Voted
DAGSTUHL
2004
15 years 4 months ago
2004
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
131
Voted
TIT
1998
15 years 3 months ago
1998
—Probability models are estimated by use of penalized log-likelihood criteria related to AIC and MDL. The accuracies of the density estimators are shown to be related to the trad...
111
Voted
EWSA
2004
Springer
15 years 9 months ago
2004
Springer
Abstract. Software architectures are engineering artifacts which provide high-level descriptions of complex systems. Certain recent architecture description languages (Adls) allow ...
128
click to vote
AAAI
2010
15 years 5 months ago
2010
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...