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» A Geometric Functional for Derivatives Approximation
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101
Voted
ICML
2007
IEEE
16 years 1 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
120
Voted
WCNC
2008
IEEE
15 years 7 months 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
86
Voted
ISCAS
1999
IEEE
73views Hardware» more  ISCAS 1999»
15 years 5 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 4 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
14 years 7 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