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ML
2002
ACM
163views Machine Learning» more  ML 2002»
13 years 8 months ago
Structural Modelling with Sparse Kernels
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
Steve R. Gunn, Jaz S. Kandola
CGF
2011
13 years 9 days ago
A Sparse Parametric Mixture Model for BTF Compression, Editing and Rendering
Bidirectional texture functions (BTFs) represent the appearance of complex materials. Three major shortcomings with BTFs are the bulky storage, the difficulty in editing and the ...
Hongzhi Wu, Julie Dorsey, Holly E. Rushmeier
AAAI
2012
11 years 11 months ago
Sparse Probabilistic Relational Projection
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Wu-Jun Li, Dit-Yan Yeung
BMCBI
2011
13 years 3 months ago
Motif-guided sparse decomposition of gene expression data for regulatory module identification
Background: Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for e...
Ting Gong, Jianhua Xuan, Li Chen, Rebecca B. Riggi...
ICASSP
2010
IEEE
13 years 9 months ago
Coherence-based near-oracle performance guarantees for sparse estimation under Gaussian noise
We consider the problem of estimating a deterministic sparse vector x0 from underdetermined measurements Ax0 + w, where w represents white Gaussian noise and A is a given determin...
Zvika Ben-Haim, Yonina C. Eldar, Michael Elad