Extrapolation-Based Prediction-Correction Methods for Time-varying Convex Optimization

نویسندگان

چکیده

In this paper, we focus on the solution of online optimization problems that arise often in signal processing and machine learning, which have access to streaming sources data. We discuss algorithms for based prediction-correction paradigm, both primal dual space. particular, leverage typical regularized least-squares structure appearing many propose a novel tailored prediction strategy, call extrapolation-based. By using tools from operator theory, then analyze convergence proposed methods as applied problems, deriving an explicit bound tracking error, is, distance time-varying optimal solution. further empirical performance algorithm when processing, robotics problems.

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ژورنال

عنوان ژورنال: Signal Processing

سال: 2023

ISSN: ['0165-1684', '1872-7557']

DOI: https://doi.org/10.1016/j.sigpro.2023.109089