A linearly convergent algorithm for sparse signal reconstruction
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Fixed Point Theory and Applications"
DOI: 10.1007/s11784-018-0635-1
Abstract: For the sparse signal reconstruction problem in compressive sensing, we propose a projection-type algorithm without any backtracking line search based on a new formulation of the problem. Under suitable conditions, global convergence and its linear… read more here.
Keywords: sparse signal; algorithm sparse; signal reconstruction; linearly convergent ... See more keywords
An Accelerated Linearly Convergent Stochastic L-BFGS Algorithm
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2891088
Abstract: The limited memory version of the Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm is the most popular quasi-Newton algorithm in machine learning and optimization. Recently, it was shown that the stochastic L-BFGS (sL-BFGS) algorithm with the variance-reduced stochastic gradient… read more here.
Keywords: stochastic bfgs; accelerated linearly; bfgs; bfgs algorithm ... See more keywords