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ADCM
2010
59views more  ADCM 2010»
15 years 6 months ago
Sampling inequalities for infinitely smooth functions, with applications to interpolation and machine learning
Sampling inequalities give a precise formulation of the fact that a differentiable function cannot attain large values, if its derivatives are bounded and if it is small on a suff...
Christian Rieger, Barbara Zwicknagl
ICASSP
2009
IEEE
16 years 1 months ago
Speech emotion recognition via a max-margin framework incorporating a loss function based on the Watson and Tellegen's emotion m
This paper considers a method for speech emotion recognition by a max-margin framework incorporating a loss function based on a well-known model called the Watson and Tellegen’s...
Sungrack Yun, Chang D. Yoo
ISSAC
2007
Springer
147views Mathematics» more  ISSAC 2007»
16 years 24 days ago
Differential equations for algebraic functions
It is classical that univariate algebraic functions satisfy linear differential equations with polynomial coefficients. Linear recurrences follow for the coefficients of their po...
Alin Bostan, Frédéric Chyzak, Bruno ...
ICMCS
2006
IEEE
155views Multimedia» more  ICMCS 2006»
16 years 20 days ago
Region-Based Image Retrieval using Radial Basis Function Network
This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified u...
Kui Wu, Kim-Hui Yap, Lap-Pui Chau
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
16 years 5 days ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett