English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper introduces tvopt, a Python framework for prototyping andbenchmarking time-varying (or online) optimization algorithms. The paper firstdescribes the theoretical approach that informed the development of tvopt. Thenit discusses the different components of the framework and their use formodeling and solving time-varying optimization problems. In particular, tvoptprovides functionalities for defining both centralized and distributed onlineproblems, and a collection of built-in algorithms to solve them, for examplegradient-based methods, ADMM and other splitting methods. Moreover, theframework implements prediction strategies to improve the accuracy of theonline solvers. The paper then proposes some numerical results on a benchmarkproblem and discusses their implementation using tvopt. The code for tvopt isavailable at https://github.com/nicola-bastianello/tvopt.

tvopt: A Python Framework for Time-Varying Optimization