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ALT
2005
Springer
14 years 5 months ago
PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance
We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Nick Palmer, Paul W. Goldberg
CICLING
2007
Springer
14 years 2 months ago
Clustering Narrow-Domain Short Texts by Using the Kullback-Leibler Distance
Clustering short length texts is a difficult task itself, but adding the narrow domain characteristic poses an additional challenge for current clustering methods. We addressed thi...
David Pinto, José-Miguel Benedí, Pao...
AI
2006
Springer
14 years 10 days ago
On the Performance of Chernoff-Distance-Based Linear Dimensionality Reduction Techniques
Abstract. We present a performance analysis of three linear dimensionality reduction techniques: Fisher's discriminant analysis (FDA), and two methods introduced recently base...
Mohammed Liakat Ali, Luis Rueda, Myriam Herrera
ICCV
2011
IEEE
12 years 8 months ago
A New Distance for Scale-Invariant 3D Shape Recognition and Registration
This paper presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transforms for...
Minh-Tri Pham, Oliver J. Woodford, Frank Perbet, A...
ICC
2007
IEEE
150views Communications» more  ICC 2007»
14 years 2 months ago
Capacity-Achieving Discrete Signaling over Additive Noise Channels
— Discrete input distributions are capacity-achieving for a variety of noise distributions whenever the input is subject to peak power or other bounding constraints. In this pape...
Anke Feiten, Rudolf Mathar