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» Approximate Learning of Dynamic Models
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BC
1999
108views more  BC 1999»
15 years 6 months ago
Exact digital simulation of time-invariant linear systems with applications to neuronal modeling
An ecient new method for the exact digital simulation of time-invariant linear systems is presented. Such systems are frequently encountered as models for neuronal systems, or as s...
Stefan Rotter, Markus Diesmann
COLT
2000
Springer
15 years 10 months ago
The Computational Complexity of Densest Region Detection
We investigate the computational complexity of the task of detecting dense regions of an unknown distribution from un-labeled samples of this distribution. We introduce a formal l...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
UAI
2008
15 years 7 months ago
Efficient Inference in Persistent Dynamic Bayesian Networks
Numerous temporal inference tasks such as fault monitoring and anomaly detection exhibit a persistence property: for example, if something breaks, it stays broken until an interve...
Tomás Singliar, Denver Dash
CGA
1999
15 years 6 months ago
Dynamics Modeling and Culling
emsintovirtualenvironments,whileabstracting the modeling process as much as possible. To achieve efficiency,weconcentrateoncullingdynamicalsystems: if the system is not in view, we...
Stephen Chenney, Jeffrey Ichnowski, David A. Forsy...
AAAI
2010
15 years 7 months ago
Integrating Sample-Based Planning and Model-Based Reinforcement Learning
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...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...