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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 8 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
ICASSP
2008
IEEE
14 years 1 months ago
Model-based sparsity projection pursuit for lattice vector quantization
In this work we present an efficient coding scheme suitable for lossy image compression using a lattice vector quantizer (LVQ) based on statistically independent data projections...
Leonardo H. Fonteles, Marc Antonini, Ronald Phlypo
MICCAI
2004
Springer
14 years 8 months ago
Solving Incrementally the Fitting and Detection Problems in fMRI Time Series
We tackle the problem of real-time statistical analysis of functional magnetic resonance imaging (fMRI) data. In a recent paper, we proposed an incremental algorithm based on the e...
Alexis Roche, Philippe Pinel, Stanislas Dehaene, J...
TSMC
2008
116views more  TSMC 2008»
13 years 7 months ago
Fuzzy Techniques for Subjective Workload-Score Modeling Under Uncertainties
This paper deals with the development of a computer model to estimate the subjective workload score of individuals by evaluating their heart-rate (HR) signals. The identification o...
Mohit Kumar, D. Arndt, Steffi Kreuzfeld, Kerstin T...
TCSV
2002
167views more  TCSV 2002»
13 years 7 months ago
Three-dimensional subband coding techniques for wireless video communications
This paper presents a new 3-D subband coding framework that is able to achieve a good balance between high compression performance and channel error resilience. Various data transf...
Hong Man, Ricardo L. de Queiroz, Mark J. T. Smith