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» Learning nonlinear dynamic models
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KR
2004
Springer
15 years 6 months ago
Learning Probabilistic Relational Planning Rules
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kae...
ICPR
2010
IEEE
15 years 6 months ago
Sparse Coding of Linear Dynamical Systems with an Application to Dynamic Texture Recognition
Given a sequence of observable features of a linear dynamical system (LDS), we propose the problem of finding a representation of the LDS which is sparse in terms of a given dict...
Bernard Ghanem, Narendra Ahuja
ESWA
2008
204views more  ESWA 2008»
15 years 1 months ago
A comparison of neural network and multiple regression analysis in modeling capital structure
Empirical studies of the variation in debt ratios across firms have used statistical models singularly to analyze the important determinants of capital structure. Researchers, how...
Hsiao-Tien Pao
AUTOMATICA
2004
112views more  AUTOMATICA 2004»
15 years 1 months ago
Ellipsoidal parameter or state estimation under model uncertainty
Ellipsoidal outer-bounding of the set of all feasible state vectors under model uncertainty is a natural extension of state estimation for deterministic models with unknown-but-bo...
Boris T. Polyak, Sergey A. Nazin, Cécile Du...
RAS
2006
111views more  RAS 2006»
15 years 1 months ago
Planning under uncertainty using model predictive control for information gathering
This paper considers trajectory planning problems for autonomous robots in information gathering tasks. The objective of the planning is to maximize the information gathered withi...
Cindy Leung, Shoudong Huang, Ngai Ming Kwok, Gamin...