{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:44:34Z","timestamp":1761597874473,"version":"3.37.3"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2017,11,2]],"date-time":"2017-11-02T00:00:00Z","timestamp":1509580800000},"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":[[2018,4]]},"DOI":"10.1007\/s10994-017-5676-y","type":"journal-article","created":{"date-parts":[[2017,11,2]],"date-time":"2017-11-02T20:34:21Z","timestamp":1509654861000},"page":"727-747","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Distributed multi-task classification: a decentralized online learning approach"],"prefix":"10.1007","volume":"107","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5735-4454","authenticated-orcid":false,"given":"Chi","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Peilin","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Shuji","family":"Hao","sequence":"additional","affiliation":[]},{"given":"Yeng Chai","family":"Soh","sequence":"additional","affiliation":[]},{"given":"Bu Sung","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Chunyan","family":"Miao","sequence":"additional","affiliation":[]},{"given":"Steven C. H.","family":"Hoi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,11,2]]},"reference":[{"key":"5676_CR1","first-page":"1817","volume":"6","author":"RK Ando","year":"2005","unstructured":"Ando, R. K., & Zhang, T. (2005). A framework for learning predictive structures from multiple tasks and unlabeled data. The Journal of Machine Learning Research, 6, 1817\u20131853.","journal-title":"The Journal of Machine Learning Research"},{"issue":"10","key":"5676_CR2","doi-asserted-by":"publisher","first-page":"5277","DOI":"10.1109\/TSP.2010.2052612","volume":"58","author":"A Bertrand","year":"2010","unstructured":"Bertrand, A., & Moonen, M. (2010). Distributed adaptive node-specific signal estimation in fully connected sensor networkspart i: Sequential node updating. IEEE Transactions on Signal Processing, 58(10), 5277\u20135291.","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"5","key":"5676_CR3","doi-asserted-by":"publisher","first-page":"2196","DOI":"10.1109\/TSP.2011.2108290","volume":"59","author":"A Bertrand","year":"2011","unstructured":"Bertrand, A., & Moonen, M. (2011). Distributed adaptive estimation of node-specific signals in wireless sensor networks with a tree topology. IEEE Transactions on Signal Processing, 59(5), 2196\u20132210.","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"1","key":"5676_CR4","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/BF02591967","volume":"27","author":"DP Bertsekas","year":"1983","unstructured":"Bertsekas, D. P. (1983). Distributed asynchronous computation of fixed points. Mathematical Programming, 27(1), 107\u2013120.","journal-title":"Mathematical Programming"},{"issue":"4","key":"5676_CR5","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1137\/S1052623495287022","volume":"7","author":"DP Bertsekas","year":"1997","unstructured":"Bertsekas, D. P. (1997). A new class of incremental gradient methods for least squares problems. SIAM Journal on Optimization, 7(4), 913\u2013926.","journal-title":"SIAM Journal on Optimization"},{"key":"5676_CR6","volume-title":"Parallel and distributed computation: Numerical methods","author":"DP Bertsekas","year":"1989","unstructured":"Bertsekas, D. P., & Tsitsiklis, J. N. (1989). Parallel and distributed computation: Numerical methods (Vol. 23). Englewood Cliffs, NJ: Prentice Hall."},{"issue":"1","key":"5676_CR7","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1137\/040615961","volume":"18","author":"D Blatt","year":"2007","unstructured":"Blatt, D., Hero, A. O., & Gauchman, H. (2007). A convergent incremental gradient method with a constant step size. SIAM Journal on Optimization, 18(1), 29\u201351.","journal-title":"SIAM Journal on Optimization"},{"key":"5676_CR8","first-page":"440","volume":"7","author":"J Blitzer","year":"2007","unstructured":"Blitzer, J., Dredze, M., Pereira, F., et al. (2007). Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. ACL, 7, 440\u2013447.","journal-title":"ACL"},{"issue":"1","key":"5676_CR9","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1023\/A:1007379606734","volume":"28","author":"R Caruana","year":"1997","unstructured":"Caruana, R. (1997). Multitask learning. Machine Learning, 28(1), 41\u201375.","journal-title":"Machine Learning"},{"key":"5676_CR10","first-page":"2901","volume":"11","author":"G Cavallanti","year":"2010","unstructured":"Cavallanti, G., Cesa-Bianchi, N., & Gentile, C. (2010). Linear algorithms for online multitask classification. The Journal of Machine Learning Research, 11, 2901\u20132934.","journal-title":"The Journal of Machine Learning Research"},{"issue":"16","key":"5676_CR11","doi-asserted-by":"publisher","first-page":"4129","DOI":"10.1109\/TSP.2014.2333560","volume":"62","author":"J Chen","year":"2014","unstructured":"Chen, J., Richard, C., & Sayed, A. H. (2014). Multitask diffusion adaptation over networks. IEEE Transactions on Signal Processing, 62(16), 4129\u20134144.","journal-title":"IEEE Transactions on Signal Processing"},{"issue":"8","key":"5676_CR12","doi-asserted-by":"publisher","first-page":"4289","DOI":"10.1109\/TSP.2012.2198470","volume":"60","author":"J Chen","year":"2012","unstructured":"Chen, J., & Sayed, A. H. (2012). Diffusion adaptation strategies for distributed optimization and learning over networks. IEEE Transactions on Signal Processing, 60(8), 4289\u20134305.","journal-title":"IEEE Transactions on Signal Processing"},{"key":"5676_CR13","first-page":"551","volume":"7","author":"K Crammer","year":"2006","unstructured":"Crammer, K., Dekel, O., Keshet, J., Shalev-Shwartz, S., & Singer, Y. (2006). Online passive\u2013aggressive algorithms. The Journal of Machine Learning Research, 7, 551\u2013585.","journal-title":"The Journal of Machine Learning Research"},{"issue":"345","key":"5676_CR14","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1080\/01621459.1974.10480137","volume":"69","author":"MH DeGroot","year":"1974","unstructured":"DeGroot, M. H. (1974). Reaching a consensus. Journal of the American Statistical Association, 69(345), 118\u2013121.","journal-title":"Journal of the American Statistical Association"},{"key":"5676_CR15","doi-asserted-by":"crossref","unstructured":"Dekel, O., Long, P. M., & Singer, Y. (2006). Online multitask learning. In G. Lugosi & H. U. Simon (Eds.), Learning theory (pp. 453\u2013467). Berlin: Springer.","DOI":"10.1007\/11776420_34"},{"issue":"2","key":"5676_CR16","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1109\/TNN.2010.2095882","volume":"22","author":"F Dinuzzo","year":"2011","unstructured":"Dinuzzo, F., Pillonetto, G., & De Nicolao, G. (2011). Client\u2013server multitask learning from distributed datasets. IEEE Transactions on Neural Networks, 22(2), 290\u2013303.","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"3","key":"5676_CR17","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1109\/TAC.2011.2161027","volume":"57","author":"JC Duchi","year":"2012","unstructured":"Duchi, J. C., Agarwal, A., & Wainwright, M. J. (2012). Dual averaging for distributed optimization: Convergence analysis and network scaling. IEEE Transactions on Automatic Control, 57(3), 592\u2013606.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"5676_CR18","first-page":"615","volume":"6","author":"T Evgeniou","year":"2005","unstructured":"Evgeniou, T., Micchelli, C. A., & Pontil, M. (2005). Learning multiple tasks with kernel methods. In Journal of Machine Learning Research, 6, 615\u2013637.","journal-title":"In Journal of Machine Learning Research"},{"key":"5676_CR19","doi-asserted-by":"crossref","unstructured":"Johansson, B., Keviczky, T., Johansson, M., & Johansson, K. H. (2008). Subgradient methods and consensus algorithms for solving convex optimization problems. In 47th IEEE conference on decision and control, 2008. CDC 2008 (pp. 4185\u20134190). IEEE.","DOI":"10.1109\/CDC.2008.4739339"},{"issue":"8","key":"5676_CR20","doi-asserted-by":"publisher","first-page":"1866","DOI":"10.1109\/TKDE.2013.139","volume":"26","author":"G Li","year":"2014","unstructured":"Li, G., Hoi, S. C., Chang, K., Liu, W., & Jain, R. (2014). Collaborative online multitask learning. IEEE Transactions on Knowledge and Data Engineering, 26(8), 1866\u20131876.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"5676_CR21","unstructured":"Lugosi, G., Papaspiliopoulos, O., & Stoltz, G. (2009). Online multi-task learning with hard constraints. arXiv preprint \n                    arXiv:0902.3526\n                    \n                  ."},{"key":"5676_CR22","unstructured":"Murugesan, K., Liu, H., Carbonell, J., & Yang, Y. (2016). Adaptive smoothed online multi-task learning. In Advances in Neural Information Processing Systems (pp. 4296\u20134304)."},{"issue":"1","key":"5676_CR23","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/TAC.2008.2009515","volume":"54","author":"A Nedic","year":"2009","unstructured":"Nedic, A., & Ozdaglar, A. (2009). Distributed subgradient methods for multi-agent optimization. IEEE Transactions on Automatic Control, 54(1), 48\u201361.","journal-title":"IEEE Transactions on Automatic Control"},{"key":"5676_CR24","first-page":"1161","volume":"21","author":"S Negahban","year":"2008","unstructured":"Negahban, S., & Wainwright, M. J. (2008). Joint support recovery under high-dimensional scaling: Benefits and perils of l1,-regularization. Advances in Neural Information Processing Systems, 21, 1161\u20131168.","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"3","key":"5676_CR25","doi-asserted-by":"publisher","first-page":"1547","DOI":"10.1137\/070711712","volume":"20","author":"ESH Neto","year":"2009","unstructured":"Neto, E. S. H., & De Pierro, \u00c1. R. (2009). Incremental subgradients for constrained convex optimization: A unified framework and new methods. SIAM Journal on Optimization, 20(3), 1547\u20131572.","journal-title":"SIAM Journal on Optimization"},{"issue":"6","key":"5676_CR26","doi-asserted-by":"publisher","first-page":"e65","DOI":"10.1371\/journal.pcbi.0020065","volume":"2","author":"B Peters","year":"2006","unstructured":"Peters, B., Bui, H. H., Frankild, S., Nielsen, M., Lundegaard, C., Kostem, E., et al. (2006). A community resource benchmarking predictions of peptide binding to mhc-i molecules. PLoS Computational Biology, 2(6), e65.","journal-title":"PLoS Computational Biology"},{"issue":"6","key":"5676_CR27","doi-asserted-by":"publisher","first-page":"3465","DOI":"10.1137\/090763184","volume":"20","author":"TK Pong","year":"2010","unstructured":"Pong, T. K., Tseng, P., Ji, S., & Ye, J. (2010). Trace norm regularization: Reformulations, algorithms, and multi-task learning. SIAM Journal on Optimization, 20(6), 3465\u20133489.","journal-title":"SIAM Journal on Optimization"},{"issue":"6","key":"5676_CR28","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1037\/h0042519","volume":"65","author":"F Rosenblatt","year":"1958","unstructured":"Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6), 386.","journal-title":"Psychological Review"},{"key":"5676_CR29","unstructured":"Saha, A., Rai, P., Venkatasubramanian, S., & Daume, H. (2011). Online learning of multiple tasks and their relationships. In International Conference on Artificial Intelligence and Statistics (pp. 643\u2013651)."},{"key":"5676_CR30","doi-asserted-by":"crossref","unstructured":"Sayed, A. H., et al. (2014). Adaptation, learning, and optimization over networks. Foundations and Trends\n                    \n                    \n                      \n                    \n                    $${\\textregistered }$$\n                    \n                      \n                        \u00ae\n                      \n                    \n                   Machine Learning, 7(4\u20135), 311\u2013801.","DOI":"10.1561\/2200000051"},{"key":"5676_CR31","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1016\/B978-0-12-411597-2.00009-6","volume":"3","author":"AH Sayed","year":"2013","unstructured":"Sayed, A. H. (2013). Diffusion adaptation over networks. Academic Press Library in Signal Processing, 3, 323\u2013454.","journal-title":"Academic Press Library in Signal Processing"},{"key":"5676_CR32","doi-asserted-by":"crossref","unstructured":"Shalev-Shwartz, S., et al. (2012). Online learning and online convex optimization. Foundations and Trends\n                    \n                    \n                      \n                    \n                    $${\\textregistered }$$\n                    \n                      \n                        \u00ae\n                      \n                    \n                   Machine Learning, 4(2), 107\u2013194.","DOI":"10.1561\/2200000018"},{"key":"5676_CR33","volume-title":"Introduction to linear algebra","author":"G Strang","year":"1993","unstructured":"Strang, G., Strang, G., Strang, G., & Strang, G. (1993). Introduction to linear algebra (Vol. 3). Wellesley, MA: Wellesley-Cambridge Press."},{"issue":"3","key":"5676_CR34","doi-asserted-by":"publisher","first-page":"516","DOI":"10.1007\/s10957-010-9737-7","volume":"147","author":"S Sundhar Ram","year":"2010","unstructured":"Sundhar Ram, S., Nedi\u0107, A., & Veeravalli, V. V. (2010). Distributed stochastic subgradient projection algorithms for convex optimization. Journal of Optimization Theory and Applications, 147(3), 516\u2013545.","journal-title":"Journal of Optimization Theory and Applications"},{"key":"5676_CR35","unstructured":"Tsitsiklis, J. N. (1984). Problems in decentralized decision making and computation. DTIC Document: Technical report."},{"issue":"12","key":"5676_CR36","doi-asserted-by":"publisher","first-page":"6217","DOI":"10.1109\/TSP.2012.2217338","volume":"60","author":"SY Tu","year":"2012","unstructured":"Tu, S. Y., & Sayed, A. H. (2012). Diffusion strategies outperform consensus strategies for distributed estimation over adaptive networks. IEEE Transactions on Signal Processing, 60(12), 6217\u20136234.","journal-title":"IEEE Transactions on Signal Processing"},{"key":"5676_CR37","unstructured":"Wang, J., Kolar, M., & Srebro, N. (2016). Distributed multi-task learning with shared representation. arXiv preprint \n                    arXiv:1603.02185\n                    \n                  ."},{"key":"5676_CR38","unstructured":"Wang, J., Kolar, M., Srebro, N., et\u00a0al. (2016). Distributed multi-task learning. In Proceedings of the 19th international conference on artificial intelligence and statistics (AISTATS) (pp. 751\u2013760)."},{"key":"5676_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, C., Zhao, P., Hao, S., Soh, Y. C., & Lee, B. S. (2016). Rom: A robust online multi-task learning approach. In Data mining (ICDM), 2016 IEEE 16th international conference on (pp. 1341\u20131346). IEEE.","DOI":"10.1109\/ICDM.2016.0183"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-017-5676-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-017-5676-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-017-5676-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,11,5]],"date-time":"2018-11-05T05:28:33Z","timestamp":1541395713000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-017-5676-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,2]]},"references-count":39,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["5676"],"URL":"https:\/\/doi.org\/10.1007\/s10994-017-5676-y","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"type":"print","value":"0885-6125"},{"type":"electronic","value":"1573-0565"}],"subject":[],"published":{"date-parts":[[2017,11,2]]}}}