{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T05:21:48Z","timestamp":1743139308337,"version":"3.40.3"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319712482"},{"type":"electronic","value":"9783319712499"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-71249-9_28","type":"book-chapter","created":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T08:53:43Z","timestamp":1514537623000},"page":"460-476","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem"],"prefix":"10.1007","author":[{"given":"Shin","family":"Matsushima","sequence":"first","affiliation":[]},{"given":"Hyokun","family":"Yun","sequence":"additional","affiliation":[]},{"given":"Xinhua","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"S. V. N.","family":"Vishwanathan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,12,30]]},"reference":[{"key":"28_CR1","first-page":"1111","volume":"15","author":"A Agarwal","year":"2014","unstructured":"Agarwal, A., Chapelle, O., Dud\u00edk, M., Langford, J.: A reliable effective terascale linear learning system. JMLR 15, 1111\u20131133 (2014)","journal-title":"JMLR"},{"key":"28_CR2","unstructured":"Bertsekas, D., Tsitsiklis, J.: Parallel and Distributed Computation: Numerical Methods (1997)"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Bottou, L., Bousquet, O.: The tradeoffs of large-scale learning. In: Optimization for Machine Learning (2011)","DOI":"10.7551\/mitpress\/8996.003.0015"},{"issue":"1","key":"28_CR4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","volume":"3","author":"S Boyd","year":"2010","unstructured":"Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends ML 3(1), 1\u2013123 (2010)","journal-title":"Found. Trends ML"},{"key":"28_CR5","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441","volume-title":"Convex Optimization","author":"S Boyd","year":"2004","unstructured":"Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)"},{"key":"28_CR6","unstructured":"Bradley, J., Kyrola, A., Bickson, D., Guestrin, C.: Parallel coordinate descent for L1-regularized loss minimization. In: ICML, pp. 321\u2013328 (2011)"},{"key":"28_CR7","doi-asserted-by":"crossref","unstructured":"Chu, C.T., Kim, S.K., Lin, Y.A., Yu, Y., Bradski, G., Ng, A.Y., Olukotun, K.: Map-reduce for machine learning on multicore. In: NIPS, pp. 281\u2013288 (2006)","DOI":"10.7551\/mitpress\/7503.003.0040"},{"key":"28_CR8","first-page":"2121","volume":"12","author":"J Duchi","year":"2010","unstructured":"Duchi, J., Hazan, E., Singer, Y.: Adaptive subgradient methods for online learning and stochastic optimization. JMLR 12, 2121\u20132159 (2010)","journal-title":"JMLR"},{"key":"28_CR9","first-page":"1871","volume":"9","author":"RE Fan","year":"2008","unstructured":"Fan, R.E., Chang, J.W., Hsieh, C.J., Wang, X.R., Lin, C.J.: LIBLINEAR: a library for large linear classification. JMLR 9, 1871\u20131874 (2008)","journal-title":"JMLR"},{"key":"28_CR10","doi-asserted-by":"crossref","unstructured":"Gemulla, R., Nijkamp, E., Haas, P.J., Sismanis, Y.: Large-scale matrix factorization with distributed stochastic gradient descent. In: KDD, pp. 69\u201377 (2011)","DOI":"10.1145\/2020408.2020426"},{"key":"28_CR11","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. (2009)","DOI":"10.1007\/978-0-387-84858-7"},{"key":"28_CR12","unstructured":"Hsieh, C.J., Yu, H.F., Dhillon, I.S.: PASSCoDe: parallel asynchronous stochastic dual coordinate descent. In: ICML (2015)"},{"key":"28_CR13","doi-asserted-by":"crossref","unstructured":"Hsieh, C.J., Chang, K.W., Lin, C.J., Keerthi, S.S., Sundararajan, S.: A dual coordinate descent method for large-scale linear SVM. In: ICML, pp. 408\u2013415 (2008)","DOI":"10.1145\/1390156.1390208"},{"key":"28_CR14","unstructured":"Johnson, R., Zhang, T.: Accelerating stochastic gradient descent using predictive variance reduction. In: NIPS, pp. 315\u2013323 (2013)"},{"key":"28_CR15","unstructured":"Langford, J., Smola, A.J., Zinkevich, M.: Slow learners are fast. In: NIPS (2009)"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Li, M., Andersen, D.G., Smola, A.J., Yu, K.: Communication efficient distributed machine learning with the parameter server. In: Neural Information Processing Systems (2014)","DOI":"10.1145\/2640087.2644155"},{"issue":"3","key":"28_CR17","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1007\/BF01589116","volume":"45","author":"DC Liu","year":"1989","unstructured":"Liu, D.C., Nocedal, J.: On the limited memory BFGS method for large scale optimization. Math. Program. 45(3), 503\u2013528 (1989)","journal-title":"Math. Program."},{"issue":"1","key":"28_CR18","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1137\/S1052623499362111","volume":"12","author":"A Nedi\u0107","year":"2001","unstructured":"Nedi\u0107, A., Bertsekas, D.P.: Incremental subgradient methods for nondifferentiable optimization. SIAM J. Optim. 12(1), 109\u2013138 (2001)","journal-title":"SIAM J. Optim."},{"issue":"4","key":"28_CR19","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."},{"key":"28_CR20","doi-asserted-by":"publisher","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.: Introductory Lectures on Convex Optimization: A Basic Course. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-1-4419-8853-9"},{"key":"28_CR21","unstructured":"Recht, B., Re, C., Wright, S., Niu, F.: Hogwild: a lock-free approach to parallelizing stochastic gradient descent. In: NIPS, pp. 693\u2013701 (2011)"},{"issue":"2","key":"28_CR22","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1007\/s12532-013-0053-8","volume":"5","author":"B Recht","year":"2013","unstructured":"Recht, B., R\u00e9, C.: Parallel stochastic gradient algorithms for large-scale matrix completion. Math. Program. Comput. 5(2), 201\u2013226 (2013)","journal-title":"Math. Program. Comput."},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Sch\u00f6lkopf, B., Smola, A.J.: Learning with Kernels (2002)","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"28_CR24","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781107298019","volume-title":"Understanding Machine Learning","author":"S Shalev-Shwartz","year":"2014","unstructured":"Shalev-Shwartz, S., Ben-David, S.: Understanding Machine Learning. Cambridge University Press, Cambridge (2014)"},{"key":"28_CR25","doi-asserted-by":"crossref","unstructured":"Shalev-Shwartz, S., Singer, Y., Srebro, N.: Pegasos: Primal estimated sub-gradient solver for SVM. In: ICML (2007)","DOI":"10.1145\/1273496.1273598"},{"key":"28_CR26","unstructured":"Sonnenburg, S., Franc, V.: COFFIN: a computational framework for linear SVMs. In: ICML (2010)"},{"key":"28_CR27","first-page":"311","volume":"11","author":"CH Teo","year":"2010","unstructured":"Teo, C.H., Vishwanthan, S.V.N., Smola, A.J., Le, Q.V.: Bundle methods for regularized risk minimization. JMLR 11, 311\u2013365 (2010)","journal-title":"JMLR"},{"key":"28_CR28","unstructured":"Webb, S., Caverlee, J., Pu, C.: Introducing the webb spam corpus: using email spam to identify web spam automatically. In: CEAS (2006)"},{"key":"28_CR29","unstructured":"Yan, F., Xu, N., Qi, Y.: Parallel inference for latent Dirichlet allocation on graphics processing units. In: NIPS, pp. 2134\u20132142 (2009)"},{"key":"28_CR30","unstructured":"Yang, T.: Trading computation for communication: distributed stochastic dual coordinate ascent. In: NIPS (2013)"},{"key":"28_CR31","first-page":"975","volume":"7","author":"H Yun","year":"2014","unstructured":"Yun, H., Yu, H.F., Hsieh, C.J., Vishwanathan, S.V.N., Dhillon, I.S.: NOMAD: non-locking, stOchastic multi-machine algorithm for asynchronous and decentralized matrix completion. VLDB 7, 975\u2013986 (2014)","journal-title":"VLDB"},{"key":"28_CR32","unstructured":"Zhang, Y., Xiao, L.: DiSCO: distributed optimization for self-concordant empirical loss. In: ICML (2015)"},{"key":"28_CR33","unstructured":"Zinkevich, M., Smola, A.J., Weimer, M., Li, L.: Parallelized stochastic gradient descent. In: NIPS, pp. 2595\u20132603 (2010)"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-71249-9_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T05:28:49Z","timestamp":1719725329000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-71249-9_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319712482","9783319712499"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-71249-9_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"30 December 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Skopje","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Macedonia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ecmlpkdd2017.ijs.si\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}