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The problem of recovering low-rank matrix from only a subset of observed entries is known as the matrix completion problem. Many problems arising in compressive sensing, image processing, machine learning, can be usefully cast as this problem. In this paper, we propose an extended linearized augmented Lagrangian method of multipliers for the problem, and prove its global convergence. We show that...
EMKC is an explicit congestion control algorithm which is designed for high bandwidth delay product (BDP) networks. Although delay-independence is an appealing characteristic, the EMKC system developed in exhibits undesirable equilibrium properties and slow fairness convergence behavior. To overcome these drawbacks, we propose a new method called AEMKC (Advanced Exponential Max-Min Kelly Control)...
EMKC is an explicit congestion control algorithm which is designed for high bandwidth delay product (BDP) networks. Although delay-independence is an appealing characteristic, the EMKC system developed in exhibits undesirable equilibrium properties and slow fairness convergence behavior. To overcome these drawbacks, we propose a new method called MEMKC (Modified Exponential Max-Min Kelly Control)...
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