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ICASSP
2010
IEEE
13 years 7 months ago
Robust regression using sparse learning for high dimensional parameter estimation problems
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
Kaushik Mitra, Ashok Veeraraghavan, Rama Chellappa
IEEEMM
2007
146views more  IEEEMM 2007»
13 years 7 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
ALT
2010
Springer
13 years 9 months ago
Distribution-Dependent PAC-Bayes Priors
We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...
Guy Lever, François Laviolette, John Shawe-...
ICA
2007
Springer
14 years 1 months ago
Dictionary Learning for L1-Exact Sparse Coding
We have derived a new algorithm for dictionary learning for sparse coding in the ℓ1 exact sparse framework. The algorithm does not rely on an approximation residual to operate, b...
Mark D. Plumbley
NIPS
2000
13 years 9 months ago
Incremental and Decremental Support Vector Machine Learning
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
Gert Cauwenberghs, Tomaso Poggio