{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T14:48:03Z","timestamp":1775054883796,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030778750","type":"print"},{"value":"9783030778767","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-77876-7_10","type":"book-chapter","created":{"date-parts":[[2021,6,13]],"date-time":"2021-06-13T23:03:11Z","timestamp":1623625391000},"page":"144-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["One-Point Gradient-Free Methods for Smooth and Non-smooth Saddle-Point Problems"],"prefix":"10.1007","author":[{"given":"Aleksandr","family":"Beznosikov","sequence":"first","affiliation":[]},{"given":"Vasilii","family":"Novitskii","sequence":"additional","affiliation":[]},{"given":"Alexander","family":"Gasnikov","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,14]]},"reference":[{"key":"10_CR1","unstructured":"Akhavan, A., Pontil, M., Tsybakov, A.B.: Exploiting higher order smoothness in derivative-free optimization and continuous bandits. arXiv preprint arXiv:2006.07862 (2020)"},{"key":"10_CR2","unstructured":"Bach, F., Perchet, V.: Highly-smooth zero-th order online optimization. In: Conference on Learning Theory, pp. 257\u2013283. PMLR (2016)"},{"key":"10_CR3","unstructured":"Ben-Tal, A., Nemirovski, A.: Lectures on modern convex optimization: analysis, algorithms, and engineering applications (2019)"},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"Beznosikov, A., Gorbunov, E., Gasnikov, A.: Derivative-free method for composite optimization with applications to decentralized distributed optimization. arXiv preprint arXiv:1911.10645 (2019)","DOI":"10.1016\/j.ifacol.2020.12.2272"},{"key":"10_CR5","doi-asserted-by":"crossref","unstructured":"Beznosikov, A., Novitskii, V., Gasnikov, A.: One-point gradient-free methods for smooth and non-smooth saddle-point problems. arXiv preprint arXiv:2103.00321 (2021)","DOI":"10.1007\/978-3-030-77876-7_10"},{"key":"10_CR6","unstructured":"Beznosikov, A., Sadiev, A., Gasnikov, A.: Gradient-free methods for saddle-point problem. arXiv preprint arXiv:2005.05913 (2020)"},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"Carmon, Y., Jin, Y., Sidford, A., Tian, K.: Coordinate methods for matrix games. arXiv preprint arXiv:2009.08447 (2020)","DOI":"10.1109\/FOCS46700.2020.00035"},{"key":"10_CR8","doi-asserted-by":"publisher","unstructured":"Chen, P.Y., Zhang, H., Sharma, Y., Yi, J., Hsieh, C.J.: Zoo. In: Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security - AISec 2017 (2017). https:\/\/doi.org\/10.1145\/3128572.3140448. http:\/\/dx.doi.org\/10.1145\/3128572.3140448","DOI":"10.1145\/3128572.3140448"},{"key":"10_CR9","unstructured":"Duchi, J.C., Jordan, M.I., Wainwright, M.J., Wibisono, A.: Optimal rates for zero-order convex optimization: the power of two function evaluations. arXiv preprint arXiv:1312.2139 (2013)"},{"key":"10_CR10","unstructured":"Fazel, M., Ge, R., Kakade, S., Mesbahi, M.: Global convergence of policy gradient methods for the linear quadratic regulator. In: International Conference on Machine Learning, pp. 1467\u20131476. PMLR (2018)"},{"key":"10_CR11","doi-asserted-by":"crossref","unstructured":"Gasnikov, A.V., Krymova, E.A., Lagunovskaya, A.A., Usmanova, I.N., Fedorenko, F.A.: Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. convex and strongly-convex case. Autom. Remote Control 78(2), 224\u2013234 (2017)","DOI":"10.1134\/S0005117917020035"},{"key":"10_CR12","unstructured":"Goodfellow, I.: Nips 2016 tutorial: generative adversarial networks. arXiv preprint arXiv:1701.00160 (2016)"},{"key":"10_CR13","unstructured":"Jin, Y., Sidford, A.: Efficiently solving MDPs with stochastic mirror descent. In: Daum\u00e9 III, H., Singh, A. (eds.) Proceedings of the 37th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol. 119, pp. 4890\u20134900. PMLR, 13\u201318 July 2020"},{"issue":"2","key":"10_CR14","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1007\/s10208-015-9296-2","volume":"17","author":"Y Nesterov","year":"2017","unstructured":"Nesterov, Y., Spokoiny, V.G.: Random gradient-free minimization of convex functions. Found. Comput. Math. 17(2), 527\u2013566 (2017)","journal-title":"Found. Comput. Math."},{"key":"10_CR15","doi-asserted-by":"crossref","unstructured":"Novitskii, V., Gasnikov, A.: Improved exploiting higher order smoothness in derivative-free optimization and continuous bandit. arXiv preprint arXiv:2101.03821 (2021)","DOI":"10.1007\/s11590-022-01863-z"},{"key":"10_CR16","doi-asserted-by":"crossref","unstructured":"Sadiev, A., Beznosikov, A., Dvurechensky, P., Gasnikov, A.: Zeroth-order algorithms for smooth saddle-point problems. arXiv preprint arXiv:2009.09908 (2020)","DOI":"10.1007\/978-3-030-86433-0_5"},{"issue":"52","key":"10_CR17","first-page":"1","volume":"18","author":"O Shamir","year":"2017","unstructured":"Shamir, O.: An optimal algorithm for bandit and zero-order convex optimization with two-point feedback. J. Mach. Learn. Res. 18(52), 1\u201311 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"10_CR18","unstructured":"Zhang, Y., Zhou, Y., Ji, K., Zavlanos, M.M.: Improving the convergence rate of one-point zeroth-order optimization using residual feedback. arXiv preprint arXiv:2006.10820 (2020)"}],"container-title":["Lecture Notes in Computer Science","Mathematical Optimization Theory and Operations Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-77876-7_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,31]],"date-time":"2022-12-31T00:16:58Z","timestamp":1672445818000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-77876-7_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030778750","9783030778767"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-77876-7_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"14 June 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MOTOR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Mathematical Optimization Theory and Operations Research","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Irkutsk","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Russia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"motor2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conference.icc.ru\/e\/motor2021","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"102","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3,4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2,5","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}