{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T12:49:57Z","timestamp":1725454197447},"publisher-location":"Berlin, Heidelberg","reference-count":24,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642341052"},{"type":"electronic","value":"9783642341069"}],"license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"DOI":"10.1007\/978-3-642-34106-9_15","type":"book-chapter","created":{"date-parts":[[2012,10,1]],"date-time":"2012-10-01T05:56:27Z","timestamp":1349070987000},"page":"154-168","source":"Crossref","is-referenced-by-count":8,"title":["Efficient Protocols for Distributed Classification and Optimization"],"prefix":"10.1007","author":[{"suffix":"III","given":"Hal","family":"Daum\u00e9","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeff M.","family":"Phillips","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Avishek","family":"Saha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suresh","family":"Venkatasubramanian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"15_CR1","unstructured":"Daum\u00e9 III, H., Phillips, J., Saha, A., Venkatasubramanian, S.: Protocols for learning classifiers on distributed data. In: AISTATS 2012 (2012)"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Bekkerman, R., Bilenko, M., Langford, J. (eds.): Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press (2011)","DOI":"10.1145\/2107736.2107740"},{"key":"15_CR3","unstructured":"McDonald, R., Hall, K., Mann, G.: Distributed training strategies for the structured perceptron. In: NAACL HLT (2010)"},{"key":"15_CR4","unstructured":"Mann, G., McDonald, R., Mohri, M., Silberman, N., Walker, D.: Efficient large-scale distributed training of conditional maximum entropy models. In: NIPS (2009)"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Collins, M.: Discriminative training methods for hidden markov models: theory and experiments with perceptron algorithms. In: EMNLP (2002)","DOI":"10.3115\/1118693.1118694"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Bauer, E., Kohavi, R.: An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning\u00a036(1-2) (1999)","DOI":"10.1023\/A:1007515423169"},{"key":"15_CR7","unstructured":"Dekel, O., Gilad-Bachrach, R., Shamir, O., Xiao, L.: Optimal distributed online prediction using mini-batches. arXiv:1012.1367 (2010)"},{"key":"15_CR8","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 (2007)","DOI":"10.7551\/mitpress\/7503.003.0040"},{"key":"15_CR9","first-page":"311","volume":"11","author":"C.H. Teo","year":"2010","unstructured":"Teo, C.H., Vishwanthan, S., Smola, A.J., Le, Q.V.: Bundle methods for regularized risk minimization. J. Mach. Learn. Res.\u00a011, 311\u2013365 (2010)","journal-title":"J. Mach. Learn. Res."},{"key":"15_CR10","unstructured":"Zinkevich, M., Weimer, M., Smola, A., Li, L.: Parallelized stochastic gradient descent. In: NIPS (2010)"},{"key":"15_CR11","unstructured":"Servedio, R.A., Long, P.: Algorithms and hardness results for parallel large margin learning. In: NIPS (2011)"},{"key":"15_CR12","unstructured":"Balcan, M.F., Blum, A., Fine, S., Mansour, Y.: Distributed learning, communication complexity and privacy. In: COLT 2012, arXiv:1204.3514 (to appear, June 2012)"},{"key":"15_CR13","unstructured":"Daum\u00e9 III, H., Phillips, J.M., Saha, A., Venkatasubramanian, S.: Efficient protocols for distributed classification and optimization. arXiv:1204.3523"},{"key":"15_CR14","unstructured":"Anthony, M., Bartlett, P.L.: Neural Network Learning: Theoretical Foundations, Cambridge (2009)"},{"key":"15_CR15","unstructured":"Cormode, G., Muthukrishnan, S., Yi, K.: Algorithms for distributed functional monitoring. In: SODA (2008)"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Cormode, G., Muthukrishnan, S., Yi, K., Zhang, Q.: Optimal sampling from distributed streams. In: PODS (2010)","DOI":"10.1145\/1807085.1807099"},{"key":"15_CR17","doi-asserted-by":"crossref","unstructured":"Matousek, J.: Approximations and optimal geometric divide-and-conquer. In: STOC (1991)","DOI":"10.1145\/103418.103470"},{"key":"15_CR18","doi-asserted-by":"crossref","unstructured":"Chazelle, B.: The Discrepancy Method, Cambridge (2000)","DOI":"10.1017\/CBO9780511626371"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Matou\u0161ek, J.: Geometric Discrepancy. Springer (1999)","DOI":"10.1007\/978-3-642-03942-3"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM TIST\u00a02(3) (2011)","DOI":"10.1145\/1961189.1961199"},{"key":"15_CR21","doi-asserted-by":"crossref","unstructured":"Arora, S., Hazan, E., Kale, S.: Fast algorithms for approximate semidefinite programming using the multiplicative weights update method. In: FOCS (2005)","DOI":"10.1109\/SFCS.2005.35"},{"key":"15_CR22","doi-asserted-by":"crossref","unstructured":"Meka, R., Jain, P., Caramanis, C., Dhillon, I.S.: Rank minimization via online learning. In: ICML (2008)","DOI":"10.1145\/1390156.1390239"},{"key":"15_CR23","doi-asserted-by":"crossref","unstructured":"Muthukrishnan, S.: Data streams: algorithms and applications. Foundations and trends in theoretical computer science. Now Publishers (2005)","DOI":"10.1561\/0400000002"},{"issue":"1","key":"15_CR24","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s00454-006-1275-6","volume":"37","author":"T.M. Chan","year":"2007","unstructured":"Chan, T.M., Chen, E.Y.: Multi-pass geometric algorithms. Disc. & Comp. Geom.\u00a037(1), 79\u2013102 (2007)","journal-title":"Disc. & Comp. Geom."}],"container-title":["Lecture Notes in Computer Science","Algorithmic Learning Theory"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-34106-9_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,29]],"date-time":"2024-04-29T22:49:16Z","timestamp":1714430956000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-34106-9_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"ISBN":["9783642341052","9783642341069"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-34106-9_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2012]]}}}