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JMLR
2010
140views more  JMLR 2010»
13 years 3 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
ICRA
2006
IEEE
98views Robotics» more  ICRA 2006»
14 years 3 months ago
Sensor Selection and Placement for Failure Diagnosis in Networked Aerial Robots
Abstract—Unmanned aerial vehicles (UAVs) represent an important class of networked robotic applications that must be both highly dependable and autonomous. This paper addresses s...
Nagarajan Kandasamy, Fadi A. Aloul, Tak-John Koo
WSC
2004
13 years 10 months ago
An Experimental Study on Forecasting Using TES Processes
Forecasting is of prime importance for accuracy in decision making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor ...
Abdullah S. Karaman, Tayfur Altiok
GECCO
2005
Springer
115views Optimization» more  GECCO 2005»
14 years 2 months ago
A generator for hierarchical problems
We describe a generator for hierarchical problems called the Hierarchical Problem Generator (HPG). Hierarchical problems are of interest since they constitute a class of problems ...
Edwin D. de Jong, Richard A. Watson, Dirk Thierens
WG
1998
Springer
14 years 1 months ago
Integral Uniform Flows in Symmetric Networks
We study the integral uniform (multicommodity) flow problem in a graph G and construct a fractional solution whose properties are invariant under the action of a group of automorp...
Farhad Shahrokhi, László A. Sz&eacut...