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» A Geometric Functional for Derivatives Approximation
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ICML
2007
IEEE
16 years 6 months ago
Incremental Bayesian networks for structure prediction
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
Ivan Titov, James Henderson
WCNC
2008
IEEE
16 years 9 days ago
Exact BER Performance of Asynchronous MC-DS-CDMA over Nakagami-m Fading Channels
—In this contribution an accurate average bit error rate (BER) formula is derived for Nakagami-faded MC-DSCDMA in the context of asynchronous transmissions and random spreading s...
Besma Smida, Lajos Hanzo, Sofiène Affes
ISCAS
1999
IEEE
73views Hardware» more  ISCAS 1999»
15 years 10 months ago
Correlation learning rule in floating-gate pFET synapses
We study the weight dynamics of the floating-gate pFET synapse and the effects of the pFET's gate and drain voltages on these dynamics. We show that we can derive a weight upd...
Paul E. Hasler, Jeff Dugger
SIGGRAPH
1993
ACM
15 years 10 months ago
Radiosity algorithms using higher order finite element methods
Many of the current radiosity algorithms create a piecewise constant approximation to the actual radiosity. Through interpolation and extrapolation, a continuous solution is obtai...
Roy Troutman, Nelson L. Max
ACCV
2010
Springer
15 years 1 months ago
One-Class Classification with Gaussian Processes
Detecting instances of unknown categories is an important task for a multitude of problems such as object recognition, event detection, and defect localization. This paper investig...
Michael Kemmler, Erik Rodner, Joachim Denzler