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» Minimization of an M-convex Function
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TSP
2008
97views more  TSP 2008»
15 years 5 months ago
Risk-Sensitive Particle Filters for Mitigating Sample Impoverishment
Risk-sensitive filters (RSF) put a penalty to higher-order moments of the estimation error compared to conventional filters as the Kalman filter minimizing the mean square error. ...
Umut Orguner, Fredrik Gustafsson
JMLR
2002
137views more  JMLR 2002»
15 years 5 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller
SIAMCO
2002
71views more  SIAMCO 2002»
15 years 5 months ago
Rate of Convergence for Constrained Stochastic Approximation Algorithms
There is a large literature on the rate of convergence problem for general unconstrained stochastic approximations. Typically, one centers the iterate n about the limit point then...
Robert Buche, Harold J. Kushner
TIP
2002
131views more  TIP 2002»
15 years 5 months ago
Optimal edge-based shape detection
Abstract--We propose an approach to accurately detecting twodimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-d...
Hankyu Moon, Rama Chellappa, Azriel Rosenfeld
COR
2007
106views more  COR 2007»
15 years 5 months ago
On a stochastic sequencing and scheduling problem
We present a framework for solving multistage pure 0–1 programs for a widely used sequencing and scheduling problem with uncertainty in the objective function coefficients, the...
Antonio Alonso-Ayuso, Laureano F. Escudero, M. Ter...