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ICPR
2010
IEEE
15 years 11 days 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
WSC
1997
14 years 11 months ago
Modeling Dependencies in Stochastic Simulation Inputs
We discuss some basic techniques for modeling dependence between the random variables that are inputs to a simulation model, with the main emphasis being continuous bivariate dist...
James R. Wilson
CCE
2006
14 years 10 months ago
An efficient algorithm for large scale stochastic nonlinear programming problems
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
Y. Shastri, Urmila M. Diwekar
FS
2010
140views more  FS 2010»
14 years 8 months ago
Nonparametric estimation for a stochastic volatility model
Abstract Consider discrete time observations (X δ)1≤ ≤n+1 of the process X satisfying dXt = √ VtdBt, with Vt a one-dimensional positive diffusion process independent of the...
F. Comte, V. Genon-Catalot, Yves Rozenholc
CDC
2010
IEEE
102views Control Systems» more  CDC 2010»
14 years 5 months ago
Stock market trading via stochastic network optimization
We consider the problem of dynamic buying and selling of shares from a collection of N stocks with random price fluctuations. To limit investment risk, we place an upper bound on t...
Michael J. Neely