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» The Complexity of Iterated Multiplication
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ECCV
2010
Springer
14 years 10 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
TASLP
2010
134views more  TASLP 2010»
14 years 4 months ago
Multiple Fundamental Frequency Estimation by Modeling Spectral Peaks and Non-Peak Regions
This paper presents a maximum likelihood approach to multiple fundamental frequency (F0) estimation for a mixture of harmonic sound sources, where the power spectrum of a time fra...
Zhiyao Duan, Bryan Pardo, Changshui Zhang
IPL
2006
93views more  IPL 2006»
14 years 10 months ago
A decidable characterization of the classes between lintime and exptime
A language is defined by closure under safe iteration and under a new form of safe diagonalization that, unlike other forms of diagonalization used in literature to define sub-recu...
Salvatore Caporaso
VTC
2008
IEEE
115views Communications» more  VTC 2008»
15 years 4 months ago
Graph-Based Turbo DeCodulation with LDPC Codes
—Turbo DeCodulation is the combination of iterative demodulation and iterative source-channel decoding in a multiple Turbo process. The receiver structures of bit-interleaved cod...
Birgit Schotsch, Laurent Schmalen, Peter Vary, Tho...
INFOCOM
2011
IEEE
14 years 1 months ago
Consort: Node-Constrained Opportunistic Routing in wireless mesh networks
— Opportunistic routing is proposed to improve the performance of wireless networks by exploiting the broadcast nature and spatial diversity of the wireless medium. In this paper...
Xi Fang, Dejun Yang, Guoliang Xue