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» Discrete stochastic optimization using linear interpolation
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ICPR
2010
IEEE
13 years 11 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
TIT
2011
157views more  TIT 2011»
13 years 3 months ago
Decentralized Sequential Hypothesis Testing Using Asynchronous Communication
—An asymptotically optimum test for the problem of decentralized sequential hypothesis testing is presented. The induced communication between sensors and fusion center is asynch...
Georgios Fellouris, George V. Moustakides
AUTOMATICA
2008
90views more  AUTOMATICA 2008»
13 years 8 months ago
On the infinite time solution to state-constrained stochastic optimal control problems
: For an infinite-horizon optimal control problem, the cost does not, in general, converge. The classical work-around to this problem is to introduce a discount or "forgetting...
Per Rutquist, Claes Breitholtz, Torsten Wik
WSC
2008
13 years 11 months ago
Simulation and optimization in a health center in Medellin, Colombia
Simulation has been widely applied to health care cases in numerous countries. In Colombia, these applications are scarce. We use a systemic approach, discrete event simulation, s...
Karol Perez, Laura Cardona, Sebastian Gomez, Tomas...
ICML
2009
IEEE
14 years 9 months ago
A stochastic memoizer for sequence data
We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
Frank Wood, Cédric Archambeau, Jan Gasthaus...