398 search results - page 1 / 80 » An efficient algorithm for a class of fused lasso problems |
KDD
2010
ACM
13 years 6 months ago
2010
ACM
The fused Lasso penalty enforces sparsity in both the coefficients and their successive differences, which is desirable for applications with features ordered in some meaningful w...
CORR
2010
Springer
13 years 4 months ago
2010
Springer
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
JMLR
2010
12 years 11 months ago
2010
We propose a novel group regularization which we call exclusive lasso. Unlike the group lasso regularizer that assumes covarying variables in groups, the proposed exclusive lasso ...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
Group-Lasso estimators, useful in many applications, suffer from lack of meaningful variance estimates for regression coefficients. To overcome such problems, we propose a full Ba...
TSP
2010
12 years 11 months ago
2010
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....