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ICPR
2008
IEEE
14 years 6 months ago
K-means clustering of proportional data using L1 distance
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
ICASSP
2011
IEEE
12 years 9 months ago
Sparse channel estimation with lp-norm and reweighted l1-norm penalized least mean squares
The least mean squares (LMS) algorithm is one of the most popular recursive parameter estimation methods. In its standard form it does not take into account any special characteri...
Omid Taheri, Sergiy A. Vorobyov
ICML
2007
IEEE
14 years 6 months ago
Scalable training of L1-regularized log-linear models
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
Galen Andrew, Jianfeng Gao
FOCS
2007
IEEE
13 years 11 months ago
Linear Equations Modulo 2 and the L1 Diameter of Convex Bodies
We design a randomized polynomial time algorithm which, given a 3-tensor of real numbers A = {aijk}n i,j,k=1 such that for all i, j, k ∈ {1, . . . , n} we have ai jk = aik j = a...
Subhash Khot, Assaf Naor
JMLR
2010
104views more  JMLR 2010»
13 years 1 days ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic