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» Robust Probabilistic Inference in Distributed Systems
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ESANN
2007
13 years 9 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
AGENTS
2001
Springer
14 years 8 hour ago
Monitoring deployed agent teams
Recent years are seeing an increasing need for on-line monitoring of deployed distributed teams of cooperating agents, e.g., for visualization, or performance tracking. However, i...
Gal A. Kaminka, David V. Pynadath, Milind Tambe
ICML
2010
IEEE
13 years 7 months ago
FAB-MAP: Appearance-Based Place Recognition and Mapping using a Learned Visual Vocabulary Model
We present an overview of FAB-MAP, an algorithm for place recognition and mapping developed for infrastructure-free mobile robot navigation in large environments. The system allow...
Mark Joseph Cummins, Paul M. Newman
CODES
2010
IEEE
13 years 5 months ago
Statistical approach in a system level methodology to deal with process variation
The impact of process variation in state of the art technology makes traditional (worst case) designs unnecessarily pessimistic, which translates to suboptimal designs in terms of...
Concepción Sanz Pineda, Manuel Prieto, Jos&...
SIGMOD
2006
ACM
156views Database» more  SIGMOD 2006»
14 years 7 months ago
MauveDB: supporting model-based user views in database systems
Real-world data -- especially when generated by distributed measurement infrastructures such as sensor networks -- tends to be incomplete, imprecise, and erroneous, making it impo...
Amol Deshpande, Samuel Madden