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Sparse group lasso and high dimensional multinomial classification

Vincent, Martin; Hansen, Niels Richard - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 771-786

The sparse group lasso optimization problem is solved using a coordinate gradient descent algorithm. The algorithm is …

Persistent link: https://www.econbiz.de/10011056479

Edge-based semidefinite programming relaxation of sensor network localization with lower bound constraints

Pong, Ting - In: Computational Optimization and Applications 53 (2012) 1, pp. 23-44

In this paper, we strengthen the edge-based semidefinite programming relaxation (ESDP) recently proposed by Wang, Zheng, Boyd, and Ye (SIAM J. Optim. 19:655–673, <CitationRef CitationID="CR28">2008</CitationRef>) by adding lower bound constraints. We show that, when distances are exact, zero individual trace is necessary and sufficient...</citationref>

Persistent link: https://www.econbiz.de/10010998374

A coordinate gradient descent method for linearly constrained smooth optimization and support vector machines training

Tseng, Paul; Yun, Sangwoon - In: Computational Optimization and Applications 47 (2010) 2, pp. 179-206

Persistent link: https://www.econbiz.de/10008674177