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» Prediction on Spike Data Using Kernel Algorithms
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DAC
2008
ACM
16 years 7 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
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
16 years 25 days 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 6 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 8 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»
15 years 1 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