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» The Convergence of Iterated Classification
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ICIP
2005
IEEE
16 years 2 months ago
An adaptive segmentation-based regularization term for image restoration
This paper proposes an original inhomogeneous restoration (deconvolution) model under the Bayesian framework. In this model, regularization is achieved, during the iterative resto...
Max Mignotte
117
Voted
JMLR
2011
110views more  JMLR 2011»
14 years 7 months ago
Training SVMs Without Offset
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Ingo Steinwart, Don R. Hush, Clint Scovel
84
Voted
CDC
2008
IEEE
123views Control Systems» more  CDC 2008»
15 years 7 months ago
On distributed averaging algorithms and quantization effects
—We consider distributed iterative algorithms for the averaging problem over time-varying topologies. Our focus is on the convergence time of such algorithms when complete (unqua...
Angelia Nedic, Alexander Olshevsky, Asuman E. Ozda...
104
Voted
INFOCOM
2008
IEEE
15 years 7 months ago
Which Distributed Averaging Algorithm Should I Choose for my Sensor Network?
Average consensus and gossip algorithms have recently received significant attention, mainly because they constitute simple and robust algorithms for distributed information proc...
Patrick Denantes, Florence Bénézit, ...
107
Voted
ICML
2009
IEEE
16 years 1 months ago
ABC-boost: adaptive base class boost for multi-class classification
We propose abc-boost (adaptive base class boost) for multi-class classification and present abc-mart, an implementation of abcboost, based on the multinomial logit model. The key ...
Ping Li