{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T02:59:57Z","timestamp":1649127597687},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2015,9,25]],"date-time":"2015-09-25T00:00:00Z","timestamp":1443139200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2016,4]]},"DOI":"10.1007\/s10994-015-5531-y","type":"journal-article","created":{"date-parts":[[2015,9,25]],"date-time":"2015-09-25T14:41:33Z","timestamp":1443192093000},"page":"1-26","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Lower bounds on individual sequence regret"],"prefix":"10.1007","volume":"103","author":[{"given":"Eyal","family":"Gofer","sequence":"first","affiliation":[]},{"given":"Yishay","family":"Mansour","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,9,25]]},"reference":[{"key":"5531_CR1","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511804441","volume-title":"Convex optimization","author":"S Boyd","year":"2004","unstructured":"Boyd, S., & Vandenberghe, L. (2004). Convex optimization. Cambridge: Cambridge University Press."},{"key":"5531_CR2","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511546921","volume-title":"Prediction, learning, and games","author":"N Cesa-Bianchi","year":"2006","unstructured":"Cesa-Bianchi, N., & Lugosi, G. (2006). Prediction, learning, and games. Cambridge: Cambridge University Press."},{"issue":"2\u20133","key":"5531_CR3","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1007\/s10994-006-5001-7","volume":"66","author":"N Cesa-Bianchi","year":"2007","unstructured":"Cesa-Bianchi, N., Mansour, Y., & Stoltz, G. (2007). Improved second-order bounds for prediction with expert advice. Machine Learning, 66(2\u20133), 321\u2013352.","journal-title":"Machine Learning"},{"key":"5531_CR4","first-page":"6.1","volume":"23","author":"CK Chiang","year":"2012","unstructured":"Chiang, C. K., Yang, T., Lee, C. J., Mahdavi, M., Lu, C. J., Jin, R., et al. (2012). Online optimization with gradual variations. Journal of Machine Learning Research: Proceedings Track, 23, 6.1\u20136.20.","journal-title":"Journal of Machine Learning Research: Proceedings Track"},{"key":"5531_CR5","doi-asserted-by":"crossref","unstructured":"DeMarzo, P., Kremer, I., & Mansour, Y. (2006). Online trading algorithms and robust option pricing. In Proceedings of the 38th annual ACM symposium on theory of computing (pp. 477\u2013486).","DOI":"10.1145\/1132516.1132586"},{"issue":"1\u20132","key":"5531_CR6","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10994-008-5060-z","volume":"72","author":"E Even-Dar","year":"2008","unstructured":"Even-Dar, E., Kearns, M., Mansour, Y., & Wortman, J. (2008). Regret to the best vs. regret to the average. Machine Learning, 72(1\u20132), 21\u201337.","journal-title":"Machine Learning"},{"key":"5531_CR7","first-page":"210","volume":"35","author":"E Gofer","year":"2014","unstructured":"Gofer, E. (2014a). Higher-order regret bounds with switching costs. Journal of Machine Learning Research: Proceedings Track, 35, 210\u2013243.","journal-title":"Journal of Machine Learning Research: Proceedings Track"},{"key":"5531_CR8","unstructured":"Gofer, E. (2014b). Machine learning algorithms with applications in finance. PhD thesis, Tel Aviv University."},{"key":"5531_CR9","doi-asserted-by":"crossref","unstructured":"Gofer, E., & Mansour, Y. (2012). Lower bounds on individual sequence regret. In N. H. Bshouty, G. Stoltz, N. Vayatis, & T. Zeugmann (Eds.), Algorithmic learning theory (pp. 275\u2013289). Heidelberg: Springer.","DOI":"10.1007\/978-3-642-34106-9_23"},{"key":"5531_CR10","unstructured":"Hazan, E. (2006). Efficient algorithms for online convex optimization and their applications. PhD thesis, Princeton University."},{"key":"5531_CR11","volume-title":"Optimization for machine learning","author":"E Hazan","year":"2011","unstructured":"Hazan, E. (2011). The convex optimization approach to regret minimization. In S. Sra, S. Nowozin, & S. J. Wright (Eds.), Optimization for machine learning. Cambridge: MIT Press."},{"issue":"2\u20133","key":"5531_CR12","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s10994-010-5175-x","volume":"80","author":"E Hazan","year":"2010","unstructured":"Hazan, E., & Kale, S. (2010). Extracting certainty from uncertainty: Regret bounded by variation in costs. Machine Learning, 80(2\u20133), 165\u2013188.","journal-title":"Machine Learning"},{"issue":"3","key":"5531_CR13","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.jcss.2004.10.016","volume":"71","author":"A Kalai","year":"2005","unstructured":"Kalai, A., & Vempala, S. (2005). Efficient algorithms for online decision problems. Journal of Computer and System Sciences, 71(3), 291\u2013307.","journal-title":"Journal of Computer and System Sciences"},{"key":"5531_CR14","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4419-8853-9","volume-title":"Introductory lectures on convex optimization: A basic course","author":"Y Nesterov","year":"2004","unstructured":"Nesterov, Y. (2004). Introductory lectures on convex optimization: A basic course. Dordrecht: Kluwer Academic Publishers."},{"key":"5531_CR15","doi-asserted-by":"crossref","DOI":"10.1515\/9781400873173","volume-title":"Convex analysis","author":"RT Rockafellar","year":"1970","unstructured":"Rockafellar, R. T. (1970). Convex analysis. Princeton: Princeton University Press."},{"key":"5531_CR16","unstructured":"Shalev-Shwartz, S. (2007). Online learning: Theory, algorithms, and applications. PhD thesis, The Hebrew University."},{"key":"5531_CR17","unstructured":"von Sz\u00f6kefalvi Nagy, J. (1918). \u00dcber algebraische gleichungen mit lauter reellen wurzeln. Jahresbericht der Deutschen Mathematiker-Vereinigung, 27, 37\u201343."},{"key":"5531_CR18","unstructured":"Zinkevich, M. (2003). Online convex programming and generalized infinitesimal gradient ascent. In ICML (pp. 928\u2013936)."}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-015-5531-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-015-5531-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-015-5531-y","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T01:40:41Z","timestamp":1559353241000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-015-5531-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,25]]},"references-count":18,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,4]]}},"alternative-id":["5531"],"URL":"https:\/\/doi.org\/10.1007\/s10994-015-5531-y","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,9,25]]}}}