公开(公告)号：US20170111234A1

公开(公告)日：2017-04-20

申请号：US15296560

申请日：2016-10-18

Applicant: NEC Laboratories America, Inc.

Inventor： Asim Kadav ,  Renqiang Min ,  Erik Kruus ,  Cun Mu

IPC: H04L12/24 ,  G06N99/00

CPC classification number: H04L41/16 ,  G06N99/005 ,  H04L41/147

Abstract: A network device, system, and method are provided. The network device includes a processor. The processor is configured to store a local estimate and a dual variable maintaining an accumulated subgradient for the network device. The processor is further configured to collect values of the dual variable of neighboring network devices. The processor is also configured to form a convex combination with equal weight from the collected dual variable of neighboring network devices. The processor is additionally configured to add a most recent local subgradient for the network device, scaled by a scaling factor, to the convex combination to obtain an updated dual variable. The processor is further configured to update the local estimate by projecting the updated dual variable to a primal space.

公开(公告)号：US10291485B2

公开(公告)日：2019-05-14

申请号：US15296560

申请日：2016-10-18

Applicant: NEC Laboratories America, Inc.

Inventor： Asim Kadav ,  Renqiang Min ,  Erik Kruus ,  Cun Mu

IPC: H04L12/00 ,  H04L12/24 ,  G06N20/00

Abstract: A network device, system, and method are provided. The network device includes a processor. The processor is configured to store a local estimate and a dual variable maintaining an accumulated subgradient for the network device. The processor is further configured to collect values of the dual variable of neighboring network devices. The processor is also configured to form a convex combination with equal weight from the collected dual variable of neighboring network devices. The processor is additionally configured to add a most recent local subgradient for the network device, scaled by a scaling factor, to the convex combination to obtain an updated dual variable. The processor is further configured to update the local estimate by projecting the updated dual variable to a primal space.