{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T23:05:15Z","timestamp":1725750315359},"publisher-location":"Berlin, Heidelberg","reference-count":18,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642409349"},{"type":"electronic","value":"9783642409356"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013]]},"DOI":"10.1007\/978-3-642-40935-6_21","type":"book-chapter","created":{"date-parts":[[2013,9,27]],"date-time":"2013-09-27T05:14:50Z","timestamp":1380258890000},"page":"294-308","source":"Crossref","is-referenced-by-count":2,"title":["Dimension-Adaptive Bounds on Compressive FLD Classification"],"prefix":"10.1007","author":[{"given":"Ata","family":"Kab\u00e1n","sequence":"first","affiliation":[]},{"given":"Robert J.","family":"Durrant","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"21_CR1","unstructured":"Arriaga, R.I., Vempala, S.: An algorithmic theory of learning: Robust concepts and random projection. In: Proceedings of the 40th Annual Symposium on Foundations of Computer Science (FOCS), pp. 616\u2013623 (1999)"},{"key":"21_CR2","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1109\/TIT.2007.913516","volume":"54","author":"G. Biau","year":"2008","unstructured":"Biau, G., Devroye, L., Lugosi, G.: On the performance of clustering in Hilbert spaces. IEEE Transactions on Information Theory\u00a054, 781\u2013790 (2008)","journal-title":"IEEE Transactions on Information Theory"},{"key":"21_CR3","unstructured":"Dasgupta, S.: Learning mixtures of Gaussians. In: Proceedings of the 40th Annual Symposium on Foundations of Computer Science (FOCS), pp. 634\u2013644 (1999)"},{"key":"21_CR4","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1002\/rsa.10073","volume":"22","author":"S. Dasgupta","year":"2002","unstructured":"Dasgupta, S., Gupta, A.: An elementary proof of the Johnson-Lindenstrauss lemma. Random Structures and Algorithms\u00a022, 60\u201365 (2002)","journal-title":"Random Structures and Algorithms"},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Durrant, R.J., Kab\u00e1n, A.: Compressed Fisher linear discriminant analysis: Classification of randomly projected data. In: Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD (2010)","DOI":"10.1145\/1835804.1835945"},{"issue":"7","key":"21_CR6","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1016\/j.patrec.2011.09.008","volume":"33","author":"R.J. Durrant","year":"2012","unstructured":"Durrant, R.J., Kab\u00e1n, A.: A tight bound on the performance of Fisher\u2019s linear discriminant in randomly projected data spaces. ICPR 2010\u00a033(7), 911\u2013919 (2012); Special Issue on Awards from ICPR 2010","journal-title":"Pattern Recognition Letters"},{"key":"21_CR7","unstructured":"Durrant, R.J., Kab\u00e1n, A.: Error bounds for kernel Fisher linear discriminant in Gaussian Hilbert space. In: 15th International Conference on Artificial Intelligence and Statistics (AiStats), JMLR W&CP, vol.\u00a022, pp. 337\u2013345 (2012)"},{"key":"21_CR8","unstructured":"Durrant, R.J., Kab\u00e1n, A.: Sharp Generalization Error Bounds for Randomly-projected Classifiers. In: 30th International Conference on Machine Learning (ICML 2013), JMLR W&CP, vol.\u00a028(3), pp. 693\u2013701 (2013)"},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Farahmand, A., Szepesv\u00e1ri, C., Audibert, J.-Y.: Manifold-adaptive dimension estimation. In: Proceedings of the 24th Annual International Conference on Machine Learning (ICML), pp. 265\u2013272 (2007)","DOI":"10.1145\/1273496.1273530"},{"issue":"2","key":"21_CR10","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1137\/090771806","volume":"53","author":"N. Halko","year":"2011","unstructured":"Halko, N., Martisson, P.G., Tropp, J.A.: Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions. SIAM Review\u00a053(2), 217\u2013288 (2011)","journal-title":"SIAM Review"},{"key":"21_CR11","doi-asserted-by":"crossref","unstructured":"Horn, R.A., Johnson, C.R.: Matrix analysis. CUP (1985)","DOI":"10.1017\/CBO9780511810817"},{"key":"21_CR12","unstructured":"Johnson, N.L., Kotz, S., Balakrishnan, N.: Continuous univariate distributions, 2nd edn., vol.\u00a01. Wiley (1994)"},{"key":"21_CR13","unstructured":"Krishnan, S., Bhattacharyya, C., Hariharan, R.: A randomized algorithm for large scale support vector learning. In: Proceedings of the 21st Annual Conference on Neural Information Processing Systems, NIPS (2007)"},{"key":"21_CR14","unstructured":"Maniglia, S., Rhandi, A.: Gaussian measures on separable Hilbert spaces and applications. Quaderni del Dipartimento di Matematica dell\u2019 Universit\u00e0 del Salento, pp. 1-24 (2004)"},{"key":"21_CR15","series-title":"Wiley Series in Probability and Statistics","doi-asserted-by":"crossref","DOI":"10.1002\/0471725293","volume-title":"Discriminant Analysis and Statistical Pattern Recognition","author":"Geoffrey J. McLachlan","year":"1992","unstructured":"McLachlan, G.J.: Discriminant analysis and statistical pattern recognition. Wiley (1992)"},{"key":"21_CR16","unstructured":"Mika, S., Ratsch, G., Weston, J., Scholkopf, B., Mullers, K.R.: Fisher discriminant analysis with kernels. In: Proc. of the 1999 IEEE Signal Processing Society Workshop. IEEE (2002)"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Sarl\u00f3s, T.: Improved approximation algorithms for large matrices via random projections. In: Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS), pp. 143\u2013152 (2006)","DOI":"10.1109\/FOCS.2006.37"},{"key":"21_CR18","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1017\/CBO9780511794308.006","volume-title":"Compressed Sensing","author":"R. Vershynin","year":"2012","unstructured":"Vershynin, R.: Introduction to the non-asymptotic analysis of random matrices. In: Compressed Sensing, pp. 210\u2013268. Cambridge Univ. Press, Cambridge (2012)"}],"container-title":["Lecture Notes in Computer Science","Algorithmic Learning Theory"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-40935-6_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T02:29:04Z","timestamp":1564108144000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-40935-6_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"ISBN":["9783642409349","9783642409356"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-40935-6_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2013]]}}}