{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/stochastic-convex-optimization-with-bandit-1","title":"Stochastic convex optimization with bandit feedback","arxiv_id":"1107.1744","date":"2011-07-08","proceeding":"NeurIPS 2011 12","authors":["Alekh Agarwal","Dean P. Foster","Daniel Hsu","Sham M. Kakade","Alexander Rakhlin"],"abstract":"This paper addresses the problem of minimizing a convex, Lipschitz function $f$ over a convex, compact set $\\xset$ under a stochastic bandit feedback model. In this model, the algorithm is allowed to observe noisy realizations of the function value $f(x)$ at any query point $x \\in \\xset$. The quantity of interest is the regret of the algorithm, which is the sum of the function values at algorithm's query points minus the optimal function value. We demonstrate a generalization of the ellipsoid algorithm that incurs $\\otil(\\poly(d)\\sqrt{T})$ regret. Since any algorithm has regret at least $\\Omega(\\sqrt{T})$ on this problem, our algorithm is optimal in terms of the scaling with $T$.","url_abs":"https://arxiv.org/abs/1107.1744v2","url_pdf":"https://arxiv.org/pdf/1107.1744v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"stochastic-convex-optimization-with-bandit-1","repo_url":"https://github.com/jw3479/exogenous_mdps","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1107.1744","atlas_url":"https://app.syntology.ai/?focus=1107.1744","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}