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» A Geometric Functional for Derivatives Approximation
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ILP
2001
Springer
14 years 29 days ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
SIAMCO
2002
105views more  SIAMCO 2002»
13 years 8 months ago
Systems of Controlled Functional Differential Equations and Adaptive Tracking
Abstract. An adaptive servomechanism is developed in the context of the problem of approximate or practical tracking (with prescribed asymptotic accuracy), by the system output, of...
Achim Ilchmann, Eugene P. Ryan, Christopher J. San...
CSDA
2008
80views more  CSDA 2008»
13 years 8 months ago
Variational Bayesian functional PCA
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
Angelika van der Linde
CGF
2010
156views more  CGF 2010»
13 years 8 months ago
Mixed Finite Elements for Variational Surface Modeling
Many problems in geometric modeling can be described using variational formulations that define the smoothness of the shape and its behavior w.r.t. the posed modeling constraints....
Alec Jacobson, Elif Tosun, Olga Sorkine, Denis Zor...
WSC
2008
13 years 10 months ago
A rate result for simulation optimization with conditional value-at-risk constraints
We study a stochastic optimization problem that has its roots in financial portfolio design. The problem has a specified deterministic objective function and constraints on the co...
Soumyadip Ghosh