{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:33:58Z","timestamp":1750221238280,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":52,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,7,19]],"date-time":"2018-07-19T00:00:00Z","timestamp":1531958400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,7,19]]},"DOI":"10.1145\/3219819.3219967","type":"proceedings-article","created":{"date-parts":[[2018,7,19]],"date-time":"2018-07-19T13:05:12Z","timestamp":1532005512000},"page":"1627-1636","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Learning Dynamics of Decision Boundaries without Additional Labeled Data"],"prefix":"10.1145","author":[{"given":"Atsutoshi","family":"Kumagai","sequence":"first","affiliation":[{"name":"NTT Secure Platform Laboratories, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomoharu","family":"Iwata","sequence":"additional","affiliation":[{"name":"NTT Communication Science Laboratories, Kyoto, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,7,19]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2012.169"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/543613.543615"},{"key":"e_1_3_2_2_3_1","first-page":"2399","article-title":"Manifold regularization: a geometric framework for learning from labeled and unlabeled examples","author":"Belkin Mikhail","year":"2006","journal-title":"JMLR 7"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1026501525781"},{"key":"e_1_3_2_2_5_1","unstructured":"Christopher M Bishop. 2006. Pattern recognition and machine learning. springer.   Christopher M Bishop. 2006. Pattern recognition and machine learning. springer."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2551241"},{"key":"e_1_3_2_2_7_1","unstructured":"Koby Crammer Alex Kulesza and Mark Dredze. 2009. Adaptive regularization of weight vectors. In NIPS.   Koby Crammer Alex Kulesza and Mark Dredze. 2009. Adaptive regularization of weight vectors. In NIPS."},{"key":"e_1_3_2_2_8_1","unstructured":"Thang D. Bui Richard E. Turner Cuong V. Nguyen Yingzhen Li. 2018. Variational continual learning. In ICLR.  Thang D. Bui Richard E. Turner Cuong V. Nguyen Yingzhen Li. 2018. Variational continual learning. In ICLR."},{"key":"e_1_3_2_2_9_1","first-page":"12","article-title":"Compose: a semisupervised learning framework for initially labeled nonstationary streaming data. Neural Networks and Learning Systems","volume":"25","author":"Dyer Karl B","year":"2014","journal-title":"IEEE Transactions on"},{"key":"e_1_3_2_2_10_1","unstructured":"Yoav Freund Robert E Schapire etal 1996. Experiments with a new boosting algorithm. In ICML.   Yoav Freund Robert E Schapire et al. 1996. Experiments with a new boosting algorithm. In ICML."},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2523813"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Jin Gao Haibin Ling Weiming Hu and Junliang Xing. 2014. Transfer learning based visual tracking with gaussian processes regression. In ECCV.  Jin Gao Haibin Ling Weiming Hu and Junliang Xing. 2014. Transfer learning based visual tracking with gaussian processes regression. In ECCV.","DOI":"10.1007\/978-3-319-10578-9_13"},{"key":"e_1_3_2_2_13_1","unstructured":"Andrew B Goldberg Ming Li and Xiaojin Zhu. 2008. Online manifold regularization: a new learning setting and empirical study. In ECML PKDD.  Andrew B Goldberg Ming Li and Xiaojin Zhu. 2008. Online manifold regularization: a new learning setting and empirical study. In ECML PKDD."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-017-5642-8"},{"volume-title":"Deep learning","author":"Goodfellow Ian","key":"e_1_3_2_2_15_1"},{"key":"e_1_3_2_2_16_1","unstructured":"Yves Grandvalet and Yoshua Bengio. 2004. Semi-supervised learning by entropy minimization. In NIPS.   Yves Grandvalet and Yoshua Bengio. 2004. Semi-supervised learning by entropy minimization. In NIPS."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","unstructured":"Ahsanul Haque Latifur Khan and Micheal Baron. 2016. SAND: semi-supervised adaptive novel class detection and classification over data stream. In AAAI.   Ahsanul Haque Latifur Khan and Micheal Baron. 2016. SAND: semi-supervised adaptive novel class detection and classification over data stream. In AAAI.","DOI":"10.1609\/aaai.v30i1.10283"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.116"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1115\/1.3662552"},{"key":"e_1_3_2_2_20_1","unstructured":"Takafumi Kanamori Shohei Hido and Masahi Sugiyama. 2009. Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection. In NIPS.   Takafumi Kanamori Shohei Hido and Masahi Sugiyama. 2009. Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection. In NIPS."},{"volume-title":"Danilo Jimenez Rezende, and MaxWelling","year":"2014","author":"Kingma Diederik P","key":"e_1_3_2_2_21_1"},{"volume-title":"Auto-encoding variational bayes. ICLR","year":"2014","author":"Kingma Diederik P","key":"e_1_3_2_2_22_1"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.5555\/1293831.1293836"},{"key":"e_1_3_2_2_24_1","first-page":"2755","article-title":"Dynamic weighted majority: An ensemble method for drifting concepts","volume":"8","author":"Zico Kolter J","year":"2007","journal-title":"JMLR"},{"volume-title":"Proceedings of ECAI 2000 Workshop on Current Issues in Spatio-Temporal Reasoning,.","year":"2000","author":"Koychev Ivan","key":"e_1_3_2_2_25_1"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Atsutoshi Kumagai and Tomoharu Iwata. 2016. Learning future classifiers without additional data. In AAAI.   Atsutoshi Kumagai and Tomoharu Iwata. 2016. Learning future classifiers without additional data. In AAAI.","DOI":"10.24963\/ijcai.2017\/283"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"crossref","unstructured":"Atsutoshi Kumagai and Tomoharu Iwata. 2017. Learning latest classifiers without additional labeled data. In IJCAI.   Atsutoshi Kumagai and Tomoharu Iwata. 2017. Learning latest classifiers without additional labeled data. In IJCAI.","DOI":"10.24963\/ijcai.2017\/283"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Atsutoshi Kumagai and Tomoharu Iwata. 2017. Learning non-linear dynamics of decision boundaries for maintaining classification performance. In AAAI.  Atsutoshi Kumagai and Tomoharu Iwata. 2017. Learning non-linear dynamics of decision boundaries for maintaining classification performance. In AAAI.","DOI":"10.1609\/aaai.v31i1.10830"},{"key":"e_1_3_2_2_29_1","unstructured":"Peipei Li Xindong Wu and Xuegang Hu. 2010. Mining recurring concept drifts with limited labeled streaming data. In ACML.  Peipei Li Xindong Wu and Xuegang Hu. 2010. Mining recurring concept drifts with limited labeled streaming data. In ACML."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.5555\/3112655.3112866"},{"key":"e_1_3_2_2_31_1","unstructured":"Mingsheng Long Jianmin Wang and Michael I Jordan. 2017. Deep transfer learning with joint adaptation networks. In ICML.  Mingsheng Long Jianmin Wang and Michael I Jordan. 2017. Deep transfer learning with joint adaptation networks. In ICML."},{"key":"e_1_3_2_2_32_1","unstructured":"Mingsheng Long Han Zhu Jianmin Wang and Michael I Jordan. 2016. Unsupervised domain adaptation with residual transfer networks. In NIPS.   Mingsheng Long Han Zhu Jianmin Wang and Michael I Jordan. 2016. Unsupervised domain adaptation with residual transfer networks. In NIPS."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553462"},{"key":"e_1_3_2_2_34_1","unstructured":"Takeru Miyato Shin-ichi Maeda Masanori Koyama Ken Nakae and Shin Ishii. 2016. Distributional smoothing with virtual adversarial training. In ICLR.  Takeru Miyato Shin-ichi Maeda Masanori Koyama Ken Nakae and Shin Ishii. 2016. Distributional smoothing with virtual adversarial training. In ICLR."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"volume-title":"Gaussian process for machine learning","author":"Rasmussen Carl","key":"e_1_3_2_2_37_1"},{"key":"e_1_3_2_2_38_1","unstructured":"Paul Ruvolo and Eric Eaton. 2013. ELLA: an efficient lifelong learning algorithm. In ICML.   Paul Ruvolo and Eric Eaton. 2013. ELLA: an efficient lifelong learning algorithm. In ICML."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-3758(00)00115-4"},{"key":"e_1_3_2_2_40_1","unstructured":"Vin\u00edcius MA Souza Diego F Silva Jo\u00e3o Gama and Gustavo EAPA Batista. 2015. Data stream classification guided by clustering on nonstationary environments and extreme verification latency. In SDM.  Vin\u00edcius MA Souza Diego F Silva Jo\u00e3o Gama and Gustavo EAPA Batista. 2015. Data stream classification guided by clustering on nonstationary environments and extreme verification latency. In SDM."},{"key":"e_1_3_2_2_41_1","unstructured":"Peter Sykacek and Stephen J Roberts. 2003. Adaptive classification by variational Kalman filtering. In NIPS.   Peter Sykacek and Stephen J Roberts. 2003. Adaptive classification by variational Kalman filtering. In NIPS."},{"key":"e_1_3_2_2_42_1","unstructured":"Kevin Tang Vignesh Ramanathan Li Fei-Fei and Daphne Koller. 2012. Shifting weights: adapting object detectors from image to video. In NIPS.   Kevin Tang Vignesh Ramanathan Li Fei-Fei and Daphne Koller. 2012. Shifting weights: adapting object detectors from image to video. In NIPS."},{"volume-title":"LEVEL IW: Learning extreme verification latency with importance weighting. In IJCAN.","year":"2017","author":"Umer Muhammad","key":"e_1_3_2_2_43_1"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"crossref","unstructured":"Boyu Wang and Joelle Pineau. 2015. Online boosting algorithms for anytime transfer and multitask learning. In AAAI.   Boyu Wang and Joelle Pineau. 2015. Online boosting algorithms for anytime transfer and multitask learning. In AAAI.","DOI":"10.1609\/aaai.v29i1.9607"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"crossref","unstructured":"HaixunWang Wei Fan Philip S Yu and Jiawei Han. 2003. Mining concept-drifting data streams using ensemble classifiers. In SIGKDD.  HaixunWang Wei Fan Philip S Yu and Jiawei Han. 2003. Mining concept-drifting data streams using ensemble classifiers. In SIGKDD.","DOI":"10.1145\/956750.956778"},{"volume-title":"Hoi","year":"2012","author":"Zhao Peilin","key":"e_1_3_2_2_46_1"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2009.06.005"},{"key":"e_1_3_2_2_48_1","unstructured":"Friedemann Zenke Ben Poole and Surya Ganguli. 2017. Continual learning through synaptic intelligence. In ICML.  Friedemann Zenke Ben Poole and Surya Ganguli. 2017. Continual learning through synaptic intelligence. In ICML."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2009.76"},{"key":"e_1_3_2_2_50_1","unstructured":"Peilin Zhao and Steven C Hoi. 2010. OTL: a framework of online transfer learning. In ICML.   Peilin Zhao and Steven C Hoi. 2010. OTL: a framework of online transfer learning. In ICML."},{"key":"e_1_3_2_2_51_1","first-page":"17","article-title":"Bayesian inference with posterior regularization and applications to infinite latent svms","volume":"15","author":"Zhu Jun","year":"2014","journal-title":"JMLR"},{"key":"e_1_3_2_2_52_1","first-page":"27","article-title":"Active learning with drifting streaming data. Neural Networks and Learning Systems","volume":"25","author":"Zliobaite Indre","year":"2014","journal-title":"IEEE Transactions on"}],"event":{"name":"KDD '18: The 24th ACM SIGKDD International 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":"London United Kingdom","acronym":"KDD '18"},"container-title":["Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3219819.3219967","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3219819.3219967","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:07:22Z","timestamp":1750212442000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3219819.3219967"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,19]]},"references-count":52,"alternative-id":["10.1145\/3219819.3219967","10.1145\/3219819"],"URL":"https:\/\/doi.org\/10.1145\/3219819.3219967","relation":{},"subject":[],"published":{"date-parts":[[2018,7,19]]},"assertion":[{"value":"2018-07-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}