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arXiv · 1608.05401

Distributed Optimization of Convex Sum of Non-Convex Functions

Shripad Gade·Nitin H. Vaidya
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Abstract

We present a distributed solution to optimizing a convex function composed of several non-convex functions. Each non-convex function is privately stored with an agent while the agents communicate with neighbors to form a network. We show that coupled consensus and projected gradient descent algorithm proposed in [1] can optimize convex sum of non-convex functions under an additional assumption on gradient Lipschitzness. We further discuss the applications of this analysis in improving privacy in distributed optimization.

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Shripad Gade, Nitin H. Vaidya. 2016-08-18. Distributed Optimization of Convex Sum of Non-Convex Functions. https://arxiv.org/abs/1608.05401

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