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ESWA
2008
204views more  ESWA 2008»
13 years 5 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
TASLP
2008
124views more  TASLP 2008»
13 years 4 months ago
Sparse Linear Regression With Structured Priors and Application to Denoising of Musical Audio
Abstract--We describe in this paper an audio denoising technique based on sparse linear regression with structured priors. The noisy signal is decomposed as a linear combination of...
Cédric Févotte, Bruno Torrésa...
ICASSP
2011
IEEE
12 years 8 months ago
Weighted and structured sparse total least-squares for perturbed compressive sampling
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
Hao Zhu, Georgios B. Giannakis, Geert Leus
IJON
2008
156views more  IJON 2008»
13 years 4 months ago
Structural identifiability of generalized constraint neural network models for nonlinear regression
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining...
Shuang-Hong Yang, Bao-Gang Hu, Paul-Henry Courn&eg...
CSDA
2006
169views more  CSDA 2006»
13 years 4 months ago
Generalized structured additive regression based on Bayesian P-splines
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Ba...
Andreas Brezger, Stefan Lang