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KDD
2010
ACM

An efficient algorithm for a class of fused lasso problems

11 years 1 months ago
An efficient algorithm for a class of fused lasso problems
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 way. The resulting problem is, however, challenging to solve, as the fused Lasso penalty is both non-smooth and non-separable. Existing algorithms have high computational complexity and do not scale to large-size problems. In this paper, we propose an Efficient Fused Lasso Algorithm (EFLA) for optimizing this class of problems. One key building block in the proposed EFLA is the Fused Lasso Signal Approximator (FLSA). To efficiently solve FLSA, we propose to reformulate it as the problem of finding an "appropriate" subgradient of the fused penalty at the minimizer, and develop a Subgradient Finding Algorithm (SFA). We further design a restart technique to accelerate the convergence of SFA, by exploiting the special "structures" of both the original and the reformulated FLSA problems. Our emp...
Jun Liu, Lei Yuan, Jieping Ye
Added 14 Oct 2010
Updated 14 Oct 2010
Type Conference
Year 2010
Where KDD
Authors Jun Liu, Lei Yuan, Jieping Ye
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