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129
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ALT
2005
Springer
16 years 18 days 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
124
Voted
CICLING
2007
Springer
15 years 9 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...
139
Voted
AI
2006
Springer
15 years 7 months 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
155
Voted
ICCV
2011
IEEE
14 years 3 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...
136
Voted
ICC
2007
IEEE
150views Communications» more  ICC 2007»
15 years 10 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