{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:32:54Z","timestamp":1743114774843,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030198091"},{"type":"electronic","value":"9783030198107"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-19810-7_17","type":"book-chapter","created":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T14:01:20Z","timestamp":1557151280000},"page":"168-181","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The Minimization of Empirical Risk Through Stochastic Gradient Descent with Momentum Algorithms"],"prefix":"10.1007","author":[{"given":"Arindam","family":"Chaudhuri","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,5,5]]},"reference":[{"key":"17_CR1","doi-asserted-by":"publisher","DOI":"10.2200\/S00626ED1V01Y201501AIM030","volume-title":"Metric Learning","author":"A Bellet","year":"2015","unstructured":"Bellet, A., Habrard, A., Sebban, M.: Metric Learning. Morgan and Claypool Publishers, San Rafael (2015)"},{"key":"17_CR2","unstructured":"Zhao, P., Hoi, S., Jin, R., Yang, T.: AUC maximization. In: Proceedings of 28th International Conference on Machine Learning, pp. 233\u2013240 (2011)"},{"key":"17_CR3","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1007\/978-3-642-04180-8_41","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Johannes F\u00fcrnkranz","year":"2009","unstructured":"F\u00fcrnkranz, J., H\u00fcllermeier, E., Vanderlooy, S.: Binary decomposition methods for multipartite ranking. In: Proceedings of Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 359\u2013374 (2009)"},{"key":"17_CR4","unstructured":"Cl\u00e9men\u00e7on, S.: On U-processes and clustering performance. In: Proceedings of 24th International Conference on Neural Information Processing Systems, pp. 37\u201345 (2011)"},{"key":"17_CR5","volume-title":"U-Statistics: Theory and Practice","author":"AJ Lee","year":"1990","unstructured":"Lee, A.J.: U-Statistics: Theory and Practice. Marcel Dekker, New York (1990)"},{"issue":"2","key":"17_CR6","doi-asserted-by":"publisher","first-page":"844","DOI":"10.1214\/009052607000000910","volume":"36","author":"S Cl\u00e9men\u00e7on","year":"2008","unstructured":"Cl\u00e9men\u00e7on, S., Lugosi, G., Vayatis, N.: Ranking and empirical risk minimization of U-Statistics. Ann. Stat. 36(2), 844\u2013874 (2008)","journal-title":"Ann. Stat."},{"key":"17_CR7","unstructured":"Norouzi, M., Fleet, D.J., Salakhutdinov, R.: Hamming distance metric learning. In: Proceedings of 25th International Conference on Neural Information Processing Systems, pp. 1070\u20131078 (2012)"},{"key":"17_CR8","unstructured":"Kar, P., Sriperumbudur, B., Jain, P., Karnick, H.: On the generalization ability of online learning algorithms for pairwise loss functions. In: Proceedings of 30th International Conference on Machine Learning, pp. III-441\u2013III-449 (2013)"},{"issue":"3","key":"17_CR9","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1007\/s10994-014-5456-x","volume":"99","author":"Q Qian","year":"2015","unstructured":"Qian, Q., Jin, R., Yi, J., Zhang, L., Zhu, S.: Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent. Mach. Learn. 99(3), 353\u2013372 (2015)","journal-title":"Mach. Learn."},{"key":"17_CR10","unstructured":"Johnson, R., Zhang, T.: Accelerating stochastic gradient descent using predictive variance reduction. In: Proceedings of 26th International Conference on Neural Information Processing Systems, pp. 315\u2013323 (2013)"},{"key":"17_CR11","unstructured":"Le Roux, N., Schmidt, M.W., Bach, F.: A stochastic gradient method with an exponential convergence rate for finite training sets. In: Proceedings of 25th International Conference on Neural Information Processing Systems, pp. 2663\u20132671 (2012)"},{"key":"17_CR12","doi-asserted-by":"crossref","unstructured":"Mairal, J.: Incremental majorization-minimization optimization with application to large-scale machine learning. arXiv:1402.4419 (2014)","DOI":"10.1137\/140957639"},{"key":"17_CR13","unstructured":"Defazio, A., Bach, F., Lacoste-Julien, S.: SAGA: a fast-incremental gradient method with support for non-strongly convex composite objectives. In: Proceedings of 27th International Conference on Neural Information Processing Systems, pp. 1646\u20131654 (2014)"},{"key":"17_CR14","unstructured":"Needell, D., Ward, R., Srebro, N.: Stochastic gradient descent, weighted sampling and the randomized Kaczmarz algorithm. In: Proceedings of 27th International Conference on Neural Information Processing Systems, pp. 1017\u20131025 (2014)"},{"key":"17_CR15","unstructured":"Zhao, P., Zhang, T.: Stochastic optimization with importance sampling for regularized loss minimization. In: Proceedings of 32nd International Conference on Machine Learning, pp. 1\u20139 (2015)"},{"key":"17_CR16","unstructured":"Chaudhuri, A.: Some investigations on empirical risk minimization through stochastic gradient with momentum algorithms. Technical report, TR\u20139818, Samsung R&D Institute Delhi India (2018)"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Cl\u00e9men\u00e7on, S., Robbiano, S., Tressou, J.: Maximal deviations of incomplete U-processes with applications to empirical risk sampling. In: Proceedings of 13th SIAM International Conference on Data Mining, pp. 19\u201327 (2013)","DOI":"10.1137\/1.9781611972832.3"},{"key":"17_CR18","unstructured":"Bottou, L., Bousquet, O.: The tradeoffs of large-scale learning. In: Proceedings of 20th International Conference on Neural Information Processing Systems, pp. 161\u2013168 (2007)"},{"key":"17_CR19","unstructured":"https:\/\/www.csie.ntu.edu.tw\/~cjlin\/libsvmtools\/datasets\/"},{"key":"17_CR20","unstructured":"Bach, F.R., Moulines, E.: Non-asymptotic analysis of stochastic approximation algorithms for machine learning. In: Proceedings of 24th International Conference on Neural Information Processing Systems, pp. 451\u2013459 (2011)"},{"issue":"4","key":"17_CR21","doi-asserted-by":"publisher","first-page":"1574","DOI":"10.1137\/070704277","volume":"19","author":"A Nemirovski","year":"2009","unstructured":"Nemirovski, A., Juditsky, A., Lan, G., Shapiro, A.: Robust stochastic approximation approach to stochastic programming. SIAM J. Optim. 19(4), 1574\u20131609 (2009)","journal-title":"SIAM J. Optim."}],"container-title":["Advances in Intelligent Systems and Computing","Artificial Intelligence Methods in Intelligent Algorithms"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-19810-7_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,17]],"date-time":"2022-09-17T11:04:59Z","timestamp":1663412699000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-19810-7_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030198091","9783030198107"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-19810-7_17","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"5 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Science On-line Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Zlin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 April 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 April 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"csolc2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/csoc.openpublish.eu","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}