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arXiv · 2306.03949

Partial Inference in Structured Prediction

Chuyang Ke·Jean Honorio
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Abstract

In this paper, we examine the problem of partial inference in the context of structured prediction. Using a generative model approach, we consider the task of maximizing a score function with unary and pairwise potentials in the space of labels on graphs. Employing a two-stage convex optimization algorithm for label recovery, we analyze the conditions under which a majority of the labels can be recovered. We introduce a novel perspective on the Karush-Kuhn-Tucker (KKT) conditions and primal and dual construction, and provide statistical and topological requirements for partial recovery with provable guarantees.

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Chuyang Ke, Jean Honorio. 2023-06-06. Partial Inference in Structured Prediction. https://arxiv.org/abs/2306.03949

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