We propose two algorithms based on Bregman iteration and operator splitting technique for nonlocal TV regularization problems. The convergence of the algorithms is analyzed and ap...
Xiaoqun Zhang, Martin Burger, Xavier Bresson, Stan...
Sparsity constraints are now very popular to regularized inverse problems. We review several approaches which have been proposed in the last ten years to solve inverse problems su...
In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...
Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vish...
In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
— In this paper, we use the Markov Decision Process (MDP) technique to find the optimal code allocation policy in High-Speed Downlink Packet Access (HSDPA) networks. A discrete ...
Hussein Al-Zubaidy, Jerome Talim, Ioannis Lambadar...