{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:30:11Z","timestamp":1750221011459,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":28,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["1836945 1836938 1836866 1845666 1852606 1838627 1837956"],"award-info":[{"award-number":["1836945 1836938 1836866 1845666 1852606 1838627 1837956"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330962","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"1587-1595","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning"],"prefix":"10.1145","author":[{"given":"Shuyang","family":"Yu","sequence":"first","affiliation":[{"name":"Northeastern University, Shenyang, China"}]},{"given":"Bin","family":"Gu","sequence":"additional","affiliation":[{"name":"JD Finance America Corporation, Mountain View, CA, USA"}]},{"given":"Kunpeng","family":"Ning","sequence":"additional","affiliation":[{"name":"Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"given":"Haiyan","family":"Chen","sequence":"additional","affiliation":[{"name":"Nanjing University of Aeronautics and Astronautics, Nanjing, China"}]},{"given":"Jian","family":"Pei","sequence":"additional","affiliation":[{"name":"Simon Fraser University, Burnaby, Canada"}]},{"given":"Heng","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","article-title":"Large scale transductive SVMs","author":"Collobert R.","year":"2006","unstructured":"R. Collobert , F. Sinz , J. Weston , L. Bottou . 2006 . Large scale transductive SVMs . Journal of Machine Learning Research, 7 , Aug: 1687--1712. R. Collobert, F. Sinz, J. Weston, L. Bottou. 2006. Large scale transductive SVMs. Journal of Machine Learning Research, 7, Aug: 1687--1712.","journal-title":"Journal of Machine Learning Research, 7"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Glenn Fung and Olvi L Mangasarian. 2001. Semi-superyised support vector machines for unlabeled data classification. Optimization methods and software 15 (1): 29--44.  Glenn Fung and Olvi L Mangasarian. 2001. Semi-superyised support vector machines for unlabeled data classification. Optimization methods and software 15 (1): 29--44.","DOI":"10.1080\/10556780108805809"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1090\/conm\/443\/08551"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2342533"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/645329.650050"},{"key":"e_1_3_2_1_6_1","unstructured":"T. Poggio and G. Cauwenberghs. 2001. Incremental and decremental support vector machine learning. Advances in neural information processing systems 409--415.  T. Poggio and G. Cauwenberghs. 2001. Incremental and decremental support vector machine learning. Advances in neural information processing systems 409--415."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220092"},{"volume-title":"Convex optimization","author":"Boyd Stephen","key":"e_1_3_2_1_8_1","unstructured":"Stephen Boyd and Lieven Vandenberghe . 2010. Convex optimization . Cambridge university press . Stephen Boyd and Lieven Vandenberghe. 2010. Convex optimization. Cambridge university press."},{"key":"e_1_3_2_1_9_1","first-page":"57","article-title":"Semi-supervised classification by low density separation","volume":"2005","author":"Chapelle O.","year":"2005","unstructured":"O. Chapelle and A. Zien . 2005 . Semi-supervised classification by low density separation . AISTATS , 2005 : 57 -- 64 . O. Chapelle and A. Zien. 2005. Semi-supervised classification by low density separation. AISTATS, 2005: 57--64.","journal-title":"AISTATS"},{"key":"e_1_3_2_1_10_1","first-page":"200","article-title":"Transductive inference for text classification using support vector machines","volume":"99","author":"Joachims T.","year":"1999","unstructured":"T. Joachims . 1999 . Transductive inference for text classification using support vector machines . ICML , 99 : 200 -- 209 . T. Joachims. 1999. Transductive inference for text classification using support vector machines. ICML, 99: 200--209.","journal-title":"ICML"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148253"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.12.036"},{"key":"e_1_3_2_1_13_1","article-title":"Optimization techniques for semi-supervised support vector machines","author":"Chapelle Olivier","year":"2008","unstructured":"Olivier Chapelle , Vikas Sindhwani , Sathiya S. Keerthi . 2008 . Optimization techniques for semi-supervised support vector machines . Journal of Machine Learning Research, 9 , Feb: 203--233. Olivier Chapelle, Vikas Sindhwani, Sathiya S. Keerthi. 2008. Optimization techniques for semi-supervised support vector machines. Journal of Machine Learning Research, 9, Feb: 203--233.","journal-title":"Journal of Machine Learning Research, 9"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1162\/08997660360581958"},{"volume-title":"Pattern Recognition, 2000. Proceedings. 15th International Conference on, 2: 708--711","author":"Mitra Pabitra","key":"e_1_3_2_1_15_1","unstructured":"Pabitra Mitra , C. A. Murthy and Sankar K. Pal. 2000. Data condensation in large databases by incremental learning with support vector machines . Pattern Recognition, 2000. Proceedings. 15th International Conference on, 2: 708--711 . Pabitra Mitra, C. A. Murthy and Sankar K. Pal. 2000. Data condensation in large databases by incremental learning with support vector machines. Pattern Recognition, 2000. Proceedings. 15th International Conference on, 2: 708--711."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/WKDD.2010.48"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2005.850183"},{"key":"e_1_3_2_1_18_1","volume-title":"IJCAI proceedings-international joint conference on artificial intelligence, 22(3)","author":"Li S.","year":"2011","unstructured":"S. Li , Z. Wang , G. Zhou , SYM. Lee . 2011 . Semi-supervised learning for imbalanced sentiment classification . IJCAI proceedings-international joint conference on artificial intelligence, 22(3) : 1826. S. Li, Z. Wang, G. Zhou, SYM. Lee. 2011. Semi-supervised learning for imbalanced sentiment classification. IJCAI proceedings-international joint conference on artificial intelligence, 22(3): 1826."},{"volume-title":"Proceedings of the ICML, 3.","author":"Pearson R.","key":"e_1_3_2_1_19_1","unstructured":"R. Pearson , G. Goney , and J. Shwaber . 2003. Imbalanced clustering for microarray time-series . Proceedings of the ICML, 3. R. Pearson, G. Goney, and J. Shwaber. 2003. Imbalanced clustering for microarray time-series. Proceedings of the ICML, 3."},{"volume-title":"ICML 2003 workshop on learning from imbalanced data sets II","author":"Wu G.","key":"e_1_3_2_1_20_1","unstructured":"G. Wu and E. Y. Chang . 2003. Class-boundary alignment for imbalanced dataset learning . ICML 2003 workshop on learning from imbalanced data sets II , Washington, DC, 49--56. G. Wu and E. Y. Chang. 2003. Class-boundary alignment for imbalanced dataset learning. ICML 2003 workshop on learning from imbalanced data sets II, Washington, DC, 49--56."},{"key":"e_1_3_2_1_21_1","article-title":"Sparse online learning via truncated gradient","author":"Langford John","year":"2009","unstructured":"John Langford , Lihong Li , and Tong Zhang . 2009 . Sparse online learning via truncated gradient . Journal of Machine Learning Research, 10, Mar: 777--801. John Langford, Lihong Li, and Tong Zhang. 2009. Sparse online learning via truncated gradient. Journal of Machine Learning Research, 10, Mar: 777--801.","journal-title":"Journal of Machine Learning Research, 10, Mar: 777--801."},{"key":"e_1_3_2_1_22_1","unstructured":"L\u00e9on Bottou and Yann Le Cun. 2004. Large scale online learning. Advances in neural information processing systems 217--224.   L\u00e9on Bottou and Yann Le Cun. 2004. Large scale online learning. Advances in neural information processing systems 217--224."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-19066-2_45"},{"key":"e_1_3_2_1_24_1","article-title":"The entire regularization path for the support vector machine","author":"Hastie Trevor","year":"2004","unstructured":"Trevor Hastie , Saharon Rosset , Robert Tibshirani , and Ji Zhu . 2004 . The entire regularization path for the support vector machine . Journal of Machine Learning Research, 5 , Oct: 1391--1415. Trevor Hastie, Saharon Rosset, Robert Tibshirani, and Ji Zhu. 2004. The entire regularization path for the support vector machine. Journal of Machine Learning Research, 5, Oct: 1391--1415.","journal-title":"Journal of Machine Learning Research, 5"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2002077"},{"volume-title":"Minima of functions of several variables with inequalities as side constraints. M. Sc. Dissertation. Dept. of Mathematics","author":"Karush William","key":"e_1_3_2_1_26_1","unstructured":"William Karush . 1939. Minima of functions of several variables with inequalities as side constraints. M. Sc. Dissertation. Dept. of Mathematics , Univ. of Chicago . William Karush. 1939. Minima of functions of several variables with inequalities as side constraints. M. Sc. Dissertation. Dept. of Mathematics, Univ. of Chicago."},{"key":"e_1_3_2_1_27_1","unstructured":"Fabian Sinz and Matteo Roffilli. 2012. UniverSVM. http:\/\/mloss.org\/ software\/view\/19\/.  Fabian Sinz and Matteo Roffilli. 2012. UniverSVM. http:\/\/mloss.org\/ software\/view\/19\/."},{"issue":"8","key":"e_1_3_2_1_28_1","first-page":"1304","article-title":"Feasibility and finite convergence analysis for accurate on-line v-support vector machine. Neural Networks and Learning Systems","volume":"24","author":"Gu B.","year":"2013","unstructured":"B. Gu and V.S. Sheng . 2013 . Feasibility and finite convergence analysis for accurate on-line v-support vector machine. Neural Networks and Learning Systems , IEEE Transactions on , 24 ( 8 ): 1304 -- 1315 B.Gu and V.S.Sheng. 2013. Feasibility and finite convergence analysis for accurate on-line v-support vector machine. Neural Networks and Learning Systems, IEEE Transactions on, 24(8): 1304--1315","journal-title":"IEEE Transactions on"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Anchorage AK USA","acronym":"KDD '19"},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330962","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330962","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330962","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:26:04Z","timestamp":1750206364000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330962"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":28,"alternative-id":["10.1145\/3292500.3330962","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330962","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}