{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:07:40Z","timestamp":1761808060235,"version":"3.40.3"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319461274"},{"type":"electronic","value":"9783319461281"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-46128-1_49","type":"book-chapter","created":{"date-parts":[[2016,9,3]],"date-time":"2016-09-03T05:34:23Z","timestamp":1472880863000},"page":"777-794","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deep Metric Learning with Data Summarization"],"prefix":"10.1007","author":[{"given":"Wenlin","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changyou","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenlin","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Piyush","family":"Rai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lawrence","family":"Carin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,9,4]]},"reference":[{"key":"49_CR1","first-page":"1","volume":"52","author":"PK Agarwal","year":"2005","unstructured":"Agarwal, P.K., Har-Peled, S., Varadarajan, K.R.: Geometric approximation via coresets. Comb. Comput. Geom. 52, 1\u201330 (2005)","journal-title":"Comb. Comput. Geom."},{"key":"49_CR2","doi-asserted-by":"crossref","unstructured":"Aly, M., Munich, M., Perona, P.: Indexing in large scale image collections: scaling properties and benchmark. In: 2011 IEEE Workshop on Applications of Computer Vision (WACV), pp. 418\u2013425. IEEE (2011)","DOI":"10.1109\/WACV.2011.5711534"},{"key":"49_CR3","doi-asserted-by":"crossref","unstructured":"Andoni, A., Indyk, P.: Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In: 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), pp. 459\u2013468. IEEE (2006)","DOI":"10.1109\/FOCS.2006.49"},{"key":"49_CR4","doi-asserted-by":"crossref","unstructured":"Angiulli, F.: Fast condensed nearest neighbor rule. In: Proceedings of the 22nd International Conference on Machine Learning, pp. 25\u201332. ACM (2005)","DOI":"10.1145\/1102351.1102355"},{"issue":"9","key":"49_CR5","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1145\/361002.361007","volume":"18","author":"JL Bentley","year":"1975","unstructured":"Bentley, J.L.: Multidimensional binary search trees used for associative searching. Commun. ACM 18(9), 509\u2013517 (1975)","journal-title":"Commun. ACM"},{"key":"49_CR6","doi-asserted-by":"crossref","unstructured":"Beygelzimer, A., Kakade, S., Langford, J.: Cover trees for nearest neighbor. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 97\u2013104. ACM (2006)","DOI":"10.1145\/1143844.1143857"},{"key":"49_CR7","first-page":"421","volume-title":"Lecture Notes in Computer Science","author":"L\u00e9on Bottou","year":"2012","unstructured":"Bottou, L.: Stochastic gradient descent tricks. Tech. rep, Microsoft Research, Redmond, WA (2012)"},{"key":"49_CR8","doi-asserted-by":"crossref","unstructured":"Cayton, L.: Fast nearest neighbor retrieval for bregman divergences. In: Proceedings of the 25th International Conference on Machine Learning, pp. 112\u2013119. ACM (2008)","DOI":"10.1145\/1390156.1390171"},{"key":"49_CR9","doi-asserted-by":"crossref","unstructured":"Chen, W., Grangier, D., Auli, M.: Strategies for training large vocabulary neural language models (2015). arXiv preprint arXiv:1512.04906","DOI":"10.18653\/v1\/P16-1186"},{"key":"49_CR10","unstructured":"Collobert, R., Kavukcuoglu, K., Farabet, C.: Torch7: a matlab-like environment for machine learning. In: BigLearn, NIPS Workshop. No. EPFL-CONF-192376 (2011)"},{"issue":"2","key":"49_CR11","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1016\/S0031-3203(00)00184-9","volume":"35","author":"VS Devi","year":"2002","unstructured":"Devi, V.S., Murty, M.N.: An incremental prototype set building technique. Pattern Recogn. 35(2), 505\u2013513 (2002)","journal-title":"Pattern Recogn."},{"key":"49_CR12","unstructured":"Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., Darrell, T.: Decaf: a deep convolutional activation feature for generic visual recognition (2013). arXiv preprint arXiv:1310.1531"},{"issue":"3","key":"49_CR13","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1109\/TIT.1972.1054809","volume":"18","author":"G Gates","year":"1972","unstructured":"Gates, G.: The reduced nearest neighbor rule. IEEE Trans. Inf. Theory 18(3), 431\u2013433 (1972)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"49_CR14","first-page":"518","volume":"99","author":"A Gionis","year":"1999","unstructured":"Gionis, A., Indyk, P., Motwani, R., et al.: Similarity search in high dimensions via hashing. VLDB 99, 518\u2013529 (1999)","journal-title":"VLDB"},{"key":"49_CR15","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"49_CR16","unstructured":"Goldberger, J., Hinton, G.E., Roweis, S.T., Salakhutdinov, R.: Neighbourhood components analysis. In: Advances in neural information processing systems, pp. 513\u2013520 (2004)"},{"key":"49_CR17","doi-asserted-by":"crossref","unstructured":"Graves, A., Mohamed, A.R., Hinton, G.: Speech recognition with deep recurrent neural networks. In: ICASSP (2013)","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"49_CR18","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1109\/TIT.1968.1054155","volume":"14","author":"PE Hart","year":"1968","unstructured":"Hart, P.E.: The condensed nearest neighbor rule. IEEE Trans. Inf. Theory 14, 515\u2013516 (1968)","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"6","key":"49_CR19","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/MSP.2012.2205597","volume":"29","author":"G Hinton","year":"2012","unstructured":"Hinton, G., Deng, L., Yu, D., Dahl, G.E., Mohamed, A.R., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T.N., et al.: Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups. IEEE Signal Process. Magaz. 29(6), 82\u201397 (2012)","journal-title":"IEEE Signal Process. Magaz."},{"key":"49_CR20","unstructured":"Hinton, G.E., Roweis, S.T.: Stochastic neighbor embedding. In: Advances in neural information processing systems, pp. 833\u2013840 (2002)"},{"key":"49_CR21","unstructured":"Hsieh, C.J., Si, S., Dhillon, I.S.: Fast prediction for large-scale kernel machines. In: Advances in Neural Information Processing Systems, pp. 3689\u20133697 (2014)"},{"key":"49_CR22","doi-asserted-by":"crossref","unstructured":"Hu, J., Lu, J., Tan, Y.P.: Discriminative deep metric learning for face verification in the wild. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.242"},{"key":"49_CR23","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: NIPS (2012)"},{"key":"49_CR24","unstructured":"Kusner, M., Tyree, S., Weinberger, K.Q., Agrawal, K.: Stochastic neighbor compression. In: Proceedings of the 31st International Conference on Machine Learning (ICML 2014), pp. 622\u2013630 (2014)"},{"issue":"4","key":"49_CR25","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1162\/neco.1989.1.4.541","volume":"1","author":"Y LeCun","year":"1989","unstructured":"LeCun, Y., Boser, B., Denker, J.S., Henderson, D., Howard, R.E., Hubbard, W., Jackel, L.D.: Backpropagation applied to handwritten zip code recognition. Neural Comput. 1(4), 541\u2013551 (1989)","journal-title":"Neural Comput."},{"issue":"2579\u20132605","key":"49_CR26","first-page":"85","volume":"9","author":"L Van der Maaten","year":"2008","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-sne. J. Mach. Learn. Res. 9(2579\u20132605), 85 (2008)","journal-title":"J. Mach. Learn. Res."},{"key":"49_CR27","doi-asserted-by":"crossref","unstructured":"Mikolov, T., Karafi\u00e1t, M., Burget, L., Cernock\u1ef3, J., Khudanpur, S.: Recurrent neural network based language model. In: 11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010), Makuhari, Chiba, Japan, 26\u201330 September 2010, pp. 1045\u20131048 (2010)","DOI":"10.21437\/Interspeech.2010-343"},{"key":"49_CR28","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: NIPS (2013)"},{"key":"49_CR29","doi-asserted-by":"crossref","unstructured":"Mohamed, A.r., Sainath, T.N., Dahl, G., Ramabhadran, B., Hinton, G.E., Picheny, M.A.: Deep belief networks using discriminative features for phone recognition. In: ICASSP (2011)","DOI":"10.1109\/ICASSP.2011.5947494"},{"key":"49_CR30","unstructured":"Omohundro, S.M.: Five balltree construction algorithms. International Computer Science Institute Berkeley (1989)"},{"key":"49_CR31","doi-asserted-by":"crossref","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation. Tech. rep, DTIC Document (1985)","DOI":"10.21236\/ADA164453"},{"key":"49_CR32","unstructured":"Salakhutdinov, R., Hinton, G.E.: Learning a nonlinear embedding by preserving class neighbourhood structure. In: International Conference on Artificial Intelligence and Statistics, pp. 412\u2013419 (2007)"},{"key":"49_CR33","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: Facenet: a unified embedding for face recognition and clustering (2015). arXiv preprint arXiv:1503.03832","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"49_CR34","unstructured":"Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., LeCun, Y.: Overfeat: Integrated recognition, localization and detection using convolutional networks (2013). arXiv preprint arXiv:1312.6229"},{"key":"49_CR35","unstructured":"Tieleman, T., Hinton, G.E.: Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude. Tech. rep., Coursera: Neural Networks for Machine Learning (2012)"},{"key":"49_CR36","doi-asserted-by":"crossref","unstructured":"Vinyals, O., Toshev, A., Bengio, S., Erhan, D.: Show and tell: a neural image caption generator. arXiv preprint arXiv:1411.4555 (2014)","DOI":"10.1109\/CVPR.2015.7298935"},{"key":"49_CR37","doi-asserted-by":"crossref","unstructured":"Weinberger, K., Dasgupta, A., Langford, J., Smola, A., Attenberg, J.: Feature hashing for large scale multitask learning. In: ICML (2009)","DOI":"10.1145\/1553374.1553516"},{"key":"49_CR38","unstructured":"Weinberger, K.Q., Blitzer, J., Saul, L.K.: Distance metric learning for large margin nearest neighbor classification. In: Advances in neural information processing systems, pp. 1473\u20131480 (2005)"},{"key":"49_CR39","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"818","DOI":"10.1007\/978-3-319-10590-1_53","volume-title":"Computer Vision \u2013 ECCV 2014","author":"MD Zeiler","year":"2014","unstructured":"Zeiler, M.D., Fergus, R.: Visualizing and understanding convolutional networks. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014, Part I. LNCS, vol. 8689, pp. 818\u2013833. Springer, Heidelberg (2014)"},{"key":"49_CR40","doi-asserted-by":"crossref","unstructured":"Zhang, K., Tsang, I.W., Kwok, J.T.: Improved nystr\u00f6m low-rank approximation and error analysis. In: Proceedings of the 25th International Conference on Machine Learning, pp. 1232\u20131239. ACM (2008)","DOI":"10.1145\/1390156.1390311"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-46128-1_49","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,5]],"date-time":"2021-09-05T00:20:00Z","timestamp":1630801200000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-46128-1_49"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319461274","9783319461281"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-46128-1_49","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]},"assertion":[{"value":"4 September 2016","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Riva del Garda","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2016","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 September 2016","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2016","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2016","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}