{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:10:12Z","timestamp":1750205412612,"version":"3.41.0"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319574530"},{"type":"electronic","value":"9783319574547"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-57454-7_2","type":"book-chapter","created":{"date-parts":[[2017,4,22]],"date-time":"2017-04-22T12:09:31Z","timestamp":1492862971000},"page":"17-29","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Fast and Easy Regression Technique for k-NN Classification Without Using Negative Pairs"],"prefix":"10.1007","author":[{"given":"Yutaro","family":"Shigeto","sequence":"first","affiliation":[]},{"given":"Masashi","family":"Shimbo","sequence":"additional","affiliation":[]},{"given":"Yuji","family":"Matsumoto","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,4,23]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Bellet, A., Habrard, A., Sebban, M.: A survey on metric learning for feature vectors and structured data. arXiv preprint arXiv:1306.6709 (2014)","DOI":"10.1007\/978-3-031-01572-4_7"},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Davis, J.V., Kulis, B., Jain, P., Sra, S., Dhillon, I.S.: Information-theoretic metric learning. In: ICML 2007, pp. 209\u2013216 (2007)","DOI":"10.1145\/1273496.1273523"},{"key":"2_CR3","unstructured":"Dhillon, P.S., Talukdar, P.P., Crammer, K.: Learning better data representation using inference-driven metric learning. In: ACL 2010, pp. 377\u2013381 (2010)"},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Hara, K., Suzuki, I., Shimbo, M., Kobayashi, K., Fukumizu, K., Radovanovi\u0107, M.: Localized centering: reducing hubness in large-sample data. In: AAAI 2015 (2015)","DOI":"10.1609\/aaai.v29i1.9629"},{"key":"2_CR5","first-page":"519","volume":"13","author":"P Jain","year":"2012","unstructured":"Jain, P., Kulis, B., Davis, J.V., Dhillon, I.S.: Metric and kernel learning using a linear transformation. JMLR 13, 519\u2013547 (2012)","journal-title":"JMLR"},{"issue":"4","key":"2_CR6","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1561\/2200000019","volume":"5","author":"B Kulis","year":"2013","unstructured":"Kulis, B.: Metric learning: a survey. Found. Trends Mach. Learn. 5(4), 287\u2013364 (2013)","journal-title":"Found. Trends Mach. Learn."},{"key":"2_CR7","first-page":"2487","volume":"11","author":"M Radovanovi\u0107","year":"2010","unstructured":"Radovanovi\u0107, M., Nanopoulos, A., Ivanovi\u0107, M.: Hubs in space: popular nearest neighbors in high-dimensional data. JMLR 11, 2487\u20132531 (2010)","journal-title":"JMLR"},{"key":"2_CR8","first-page":"2871","volume":"13","author":"D Schnitzer","year":"2012","unstructured":"Schnitzer, D., Flexer, A., Schedl, M., Widmer, G.: Local and global scaling reduce hubs in space. JMLR 13, 2871\u20132902 (2012)","journal-title":"JMLR"},{"key":"2_CR9","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/978-3-319-23528-8_9","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Y Shigeto","year":"2015","unstructured":"Shigeto, Y., Suzuki, I., Hara, K., Shimbo, M., Matsumoto, Y.: Ridge regression, hubness, and zero-shot learning. In: Appice, A., Rodrigues, P.P., Santos Costa, V., Soares, C., Gama, J., Jorge, A. (eds.) ECML PKDD 2015. LNCS (LNAI), vol. 9284, pp. 135\u2013151. Springer, Cham (2015). doi:10.1007\/978-3-319-23528-8_9"},{"key":"2_CR10","doi-asserted-by":"crossref","unstructured":"Suzuki, I., Hara, K., Shimbo, M., Saerens, M., Fukumizu, K.: Centering similarity measures to reduce hubs. In: EMNLP 2013, pp. 613\u2013623 (2013)","DOI":"10.18653\/v1\/D13-1058"},{"key":"2_CR11","first-page":"207","volume":"10","author":"KQ Weinberger","year":"2009","unstructured":"Weinberger, K.Q., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. JMLR 10, 207\u2013244 (2009)","journal-title":"JMLR"},{"key":"2_CR12","unstructured":"Weinberger, K.Q., Tesauro, G.: Metric learning for kernel regression. In: AISTATS 2007, pp. 608\u2013615 (2007)"},{"key":"2_CR13","unstructured":"Xing, E.P., Ng, A.Y., Jordan, M.I., Russell, S.: Distance metric learning, with application to clustering with side-information. In: NIPS 2002, pp. 505\u2013512 (2002)"},{"key":"2_CR14","unstructured":"Xu, Z., Weinberger, K.Q., Chapelle, O.: Distance metric learning for kernel machines. arXiv preprint arXiv:1208.3422 (2013)"},{"key":"2_CR15","first-page":"1","volume":"13","author":"Y Ying","year":"2012","unstructured":"Ying, Y., Li, P.: Distance metric learning with eigenvalue optimization. JMLR 13, 1\u201326 (2012)","journal-title":"JMLR"}],"container-title":["Lecture Notes in Computer Science","Advances in Knowledge Discovery and Data Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-57454-7_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:45:44Z","timestamp":1750203944000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-57454-7_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319574530","9783319574547"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-57454-7_2","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":"23 April 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PAKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jeju","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","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":"23 May 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 May 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pakdd2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/pakdd2017.snu.ac.kr\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}