{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:58:33Z","timestamp":1783439913939,"version":"3.54.6"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030012694","type":"print"},{"value":"9783030012700","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-030-01270-0_30","type":"book-chapter","created":{"date-parts":[[2018,10,5]],"date-time":"2018-10-05T22:07:51Z","timestamp":1538777271000},"page":"508-523","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["LSQ++: Lower Running Time and Higher Recall in Multi-codebook Quantization"],"prefix":"10.1007","author":[{"given":"Julieta","family":"Martinez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shobhit","family":"Zakhmi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Holger H.","family":"Hoos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James J.","family":"Little","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2018,10,6]]},"reference":[{"key":"30_CR1","doi-asserted-by":"crossref","unstructured":"Ai, L., Yu, J., Guan, T., He, Y.: Efficient approximate nearest neighbor search by optimized residual vector quantization. In: International Workshop on Content-Based Multimedia Indexing (CBMI) (2014)","DOI":"10.1109\/CBMI.2014.6849842"},{"key":"30_CR2","unstructured":"Arthur, D., Vassilvitskii, S.: k-means++: the advantages of careful seeding. In: Proceedings of the Eighteenth Annual ACM-SIAM symposium on Discrete algorithms, pp. 1027\u20131035. Society for Industrial and Applied Mathematics (2007)"},{"key":"30_CR3","doi-asserted-by":"crossref","unstructured":"Babenko, A., Lempitsky, V.: Additive quantization for extreme vector compression. In: CVPR (2014)","DOI":"10.1109\/CVPR.2014.124"},{"key":"30_CR4","doi-asserted-by":"crossref","unstructured":"Babenko, A., Lempitsky, V.: Tree quantization for large-scale similarity search and classification. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7299052"},{"key":"30_CR5","unstructured":"Babenko, A., Lempitsky, V.: Efficient indexing of billion-scale datasets of deep descriptors. In: CVPR (2016)"},{"key":"30_CR6","unstructured":"Bezanson, J., Edelman, A., Karpinski, S., Shah, V.B.: Julia: a fresh approach to numerical computing. arXiv preprint arXiv:1411.1607 (2014)"},{"key":"30_CR7","doi-asserted-by":"crossref","unstructured":"Blalock, D.W., Guttag, J.V.: Bolt: accelerated data mining with fast vector compression. In: KDD (2017)","DOI":"10.1145\/3097983.3098195"},{"key":"30_CR8","doi-asserted-by":"crossref","unstructured":"Chatfield, K., Simonyan, K., Vedaldi, A., Zisserman, A.: Return of the devil in the details: delving deep into convolutional nets. In: BMVC (2014)","DOI":"10.5244\/C.28.6"},{"issue":"12","key":"30_CR9","doi-asserted-by":"publisher","first-page":"11259","DOI":"10.3390\/s101211259","volume":"10","author":"Y Chen","year":"2010","unstructured":"Chen, Y., Guan, T., Wang, C.: Approximate nearest neighbor search by residual vector quantization. Sensors 10(12), 11259\u201311273 (2010)","journal-title":"Sensors"},{"key":"30_CR10","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: CVPR (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"30_CR11","doi-asserted-by":"crossref","unstructured":"Douze, M., Szlam, A., Hariharan, B., J\u00e9gou, H.: Low-shot learning with large-scale diffusion. In: NIPS (2017)","DOI":"10.1109\/CVPR.2018.00353"},{"key":"30_CR12","unstructured":"Ge, T., He, K., Ke, Q., Sun, J.: Optimized product quantization. In: CVPR (2013)"},{"key":"30_CR13","unstructured":"Goyal, P., et al.: Accurate, large minibatch SGD: training imagenet in 1 hour. arXiv preprint arXiv:1706.02677 (2017)"},{"key":"30_CR14","unstructured":"Guo, R., Kumar, S., Choromanski, K., Simcha, D.: Quantization based fast inner product search. In: AISTATS (2016)"},{"key":"30_CR15","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/B978-155860872-6\/50020-2","volume-title":"Stochastic Local Search","author":"Holger H. Hoos","year":"2005","unstructured":"Hoos, H.H., St\u00fctzle, T.: Stochastic Local Search: Foundations and Applications. Elsevier, Amsterdam (2004)"},{"key":"30_CR16","doi-asserted-by":"crossref","unstructured":"Hu, H., et al.: Web-scale responsive visual search at bing. arXiv preprint arXiv:1802.04914 (2018)","DOI":"10.1145\/3219819.3219843"},{"issue":"1","key":"30_CR17","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1109\/TPAMI.2010.57","volume":"33","author":"H J\u00e9gou","year":"2011","unstructured":"J\u00e9gou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. TPAMI 33(1), 117\u2013128 (2011)","journal-title":"TPAMI"},{"key":"30_CR18","unstructured":"Johnson, J., Douze, M., J\u00e9gou, H.: Billion-scale similarity search with GPUs. arXiv preprint arXiv:1702.08734 (2017)"},{"key":"30_CR19","doi-asserted-by":"crossref","unstructured":"Louren\u00e7o, H.R., Martin, O.C., St\u00fctzle, T.: Iterated local search. In: Handbook of Metaheuristics, pp. 320\u2013353. Springer, Berlin (2003)","DOI":"10.1007\/0-306-48056-5_11"},{"issue":"2","key":"30_CR20","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2), 91\u2013110 (2004)","journal-title":"IJCV"},{"key":"30_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/978-3-319-46475-6_9","volume-title":"Computer Vision \u2013 ECCV 2016","author":"J Martinez","year":"2016","unstructured":"Martinez, J., Clement, J., Hoos, H.H., Little, J.J.: Revisiting additive quantization. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 137\u2013153. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_9"},{"key":"30_CR22","unstructured":"Martinez, J., Hoos, H.H., Little, J.J.: Stacked quantizers for compositional vector compression. arXiv preprint arXiv:1411.2173 (2014)"},{"key":"30_CR23","first-page":"638","volume-title":"Lecture Notes in Computer Science","author":"Julieta Martinez","year":"2016","unstructured":"Martinez, J., Hoos, H.H., Little, J.J.: Solving multi-codebook quantization in the GPU. In: ECCV Workshop on Web-Scale Vision and Social Media (VSM) (2016)"},{"key":"30_CR24","unstructured":"Mussmann, S., Levy, D., Ermon, S.: Fast amortized inference and learning in log-linear models with randomly perturbed nearest neighbor search. In: UAI (2017)"},{"issue":"151","key":"30_CR25","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1090\/S0025-5718-1980-0572855-7","volume":"35","author":"J Nocedal","year":"1980","unstructured":"Nocedal, J.: Updating quasi-newton matrices with limited storage. Math. Comput. 35(151), 773\u2013782 (1980)","journal-title":"Math. Comput."},{"key":"30_CR26","doi-asserted-by":"crossref","unstructured":"Norouzi, M., Fleet, D.J.: Cartesian k-means. In: CVPR (2013)","DOI":"10.1109\/CVPR.2013.388"},{"issue":"11","key":"30_CR27","doi-asserted-by":"publisher","first-page":"2884","DOI":"10.1109\/TKDE.2016.2597834","volume":"28","author":"EC Ozan","year":"2016","unstructured":"Ozan, E.C., Kiranyaz, S., Gabbouj, M.: Competitive quantization for approximate nearest neighbor search. IEEE Trans. Knowl. Data Eng. 28(11), 2884\u20132894 (2016)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1\u20133","key":"30_CR28","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s11263-007-0090-8","volume":"77","author":"BC Russell","year":"2008","unstructured":"Russell, B.C., Torralba, A., Murphy, K.P., Freeman, W.T.: Labelme: a database and web-based tool for image annotation. IJCV 77(1\u20133), 157\u2013173 (2008)","journal-title":"IJCV"},{"key":"30_CR29","unstructured":"Smith, S.L., Kindermans, P.J., Le, Q.V.: Don\u2019t decay the learning rate, increase the batch size. In: ICLR (2018)"},{"key":"30_CR30","doi-asserted-by":"crossref","unstructured":"Szegedy, C., et al.: Going deeper with convolutions. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"30_CR31","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1007\/978-3-319-14998-1_17","volume-title":"Multimedia Data Mining and Analytics","author":"Jingdong Wang","year":"2015","unstructured":"Wang, J., Wang, J., Ke, Q., Zeng, G., Li, S.: Fast approximate $$K$$-means via cluster closures. In: Baughman, A.K., Gao, J., Pan, J.-Y., Petrushin, V.A. (eds.) Multimedia Data Mining and Analytics, pp. 373\u2013395. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-14998-1_17"},{"key":"30_CR32","doi-asserted-by":"crossref","unstructured":"Xia, Y., He, K., Wen, F., Sun, J.: Joint inverted indexing. In: ICCV (2013)","DOI":"10.1109\/ICCV.2013.424"},{"issue":"2","key":"30_CR33","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1109\/78.124941","volume":"40","author":"K Zeger","year":"1992","unstructured":"Zeger, K., Vaisey, J., Gersho, A.: Globally optimal vector quantizer design by stochastic relaxation. IEEE Trans. Signal Process. 40(2), 310\u2013322 (1992)","journal-title":"IEEE Trans. Signal Process."},{"key":"30_CR34","unstructured":"Zhang, T., Du, C., Wang, J.: Composite quantization for approximate nearest neighbor search. In: ICML (2014)"},{"key":"30_CR35","doi-asserted-by":"crossref","unstructured":"Zhang, T., Qi, G.J., Tang, J., Wang, J.: Sparse composite quantization. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7299085"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01270-0_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T00:45:17Z","timestamp":1665017117000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-01270-0_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030012694","9783030012700"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01270-0_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"6 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Munich","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}