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» Prediction on Spike Data Using Kernel Algorithms
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DAC
2008
ACM
16 years 3 months ago
Partial order reduction for scalable testing of systemC TLM designs
A SystemC simulation kernel consists of a deterministic implementation of the scheduler, whose specification is nondeterministic. To leverage testing of a SystemC TLM design, we f...
Sudipta Kundu, Malay K. Ganai, Rajesh Gupta
119
Voted
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
15 years 8 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof
BMCBI
2006
130views more  BMCBI 2006»
15 years 2 months ago
MicroTar: predicting microRNA targets from RNA duplexes
Background: The accurate prediction of a comprehensive set of messenger RNAs (targets) regulated by animal microRNAs (miRNAs) remains an open problem. In particular, the predictio...
Rahul Thadani, Martti T. Tammi
CVPR
2008
IEEE
16 years 4 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán
TIP
2011
123views more  TIP 2011»
14 years 9 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz