{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T23:39:36Z","timestamp":1773099576125,"version":"3.50.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2010,11,16]],"date-time":"2010-11-16T00:00:00Z","timestamp":1289865600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2011,11]]},"DOI":"10.1007\/s10115-010-0358-0","type":"journal-article","created":{"date-parts":[[2010,11,15]],"date-time":"2010-11-15T17:29:09Z","timestamp":1289842149000},"page":"435-456","source":"Crossref","is-referenced-by-count":14,"title":["Multi-resolution boosting for classification and regression problems"],"prefix":"10.1007","volume":"29","author":[{"given":"Chandan K.","family":"Reddy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin-Hyeong","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2010,11,16]]},"reference":[{"key":"358_CR1","first-page":"113","volume":"1","author":"E Allwein","year":"2001","unstructured":"Allwein E, Schapire R, Singer Y (2001) Reducing multiclass to binary: a unifying approach for margin classifiers. J Mach Learn Res 1: 113\u2013141","journal-title":"J Mach Learn Res"},{"issue":"1","key":"358_CR2","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/TPAMI.2007.1140","volume":"30","author":"V Athitsos","year":"2008","unstructured":"Athitsos V, Alon J, Sclaroff S, Kollios G (2008) Boostmap: an embedding method for efficient nearest neighbor retrieval. IEEE Trans Pattern Anal Mach Intell 30(1): 89\u2013104","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1\u20132","key":"358_CR3","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1023\/A:1007515423169","volume":"36","author":"E Bauer","year":"1999","unstructured":"Bauer E, Kohavi R (1999) An empirical comparison of voting classification algorithms: bagging, boosting, and variants. Mach Learn 36(1\u20132): 105\u2013139","journal-title":"Mach Learn"},{"key":"358_CR4","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural networks for pattern recognition","author":"CM Bishop","year":"1995","unstructured":"Bishop CM (1995) Neural networks for pattern recognition. Oxford University Press, Oxford"},{"key":"358_CR5","unstructured":"Blake CL, Merz CJ (1998) UCI repository of machine learning databases. http:\/\/www.ics.uci.edu\/mlearn\/MLRepository.html , University of California, Irvine, Deptartment of Information and Computer Sciences"},{"issue":"2","key":"358_CR6","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L (1996) Bagging predictors. Mach Learn 24(2): 123\u2013140","journal-title":"Mach Learn"},{"issue":"3","key":"358_CR7","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1214\/aos\/1024691079","volume":"26","author":"L Breiman","year":"1998","unstructured":"Breiman L (1998) Arcing classifiers. Ann Stat 26(3): 801\u2013849","journal-title":"Ann Stat"},{"issue":"462","key":"358_CR8","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1198\/016214503000125","volume":"98","author":"P Buhlmann","year":"2003","unstructured":"Buhlmann P, Yu B (2003) Boosting with the l2 loss: regression and classification. J Am Stat Assoc 98(462): 324\u2013339","journal-title":"J Am Stat Assoc"},{"issue":"1\u20133","key":"358_CR9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1023\/A:1013912006537","volume":"48","author":"M Collins","year":"2002","unstructured":"Collins M, Schapire RE, Singer Y (2002) Logistic regression, adaboost and bregman distances. Mach Learn 48(1\u20133): 253\u2013285","journal-title":"Mach Learn"},{"key":"358_CR10","unstructured":"Duffy N, Helmbold D (2000) Leveraging for regression. In: Proceedings of 13th annual conference on computational learning theory. pp 208\u2013219"},{"issue":"5","key":"358_CR11","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2001","unstructured":"Friedman JH (2001) Greedy function approximation: a gradient boosting machine. Ann Stat 29(5): 1189\u20131232","journal-title":"Ann Stat"},{"issue":"2","key":"358_CR12","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1214\/aos\/1016218223","volume":"28","author":"JH Friedman","year":"2000","unstructured":"Friedman JH, Hastie T, Tibshirani R (2000) Additive logistic regression: a statistical view of boosting. Ann Stat 28(2): 337\u2013407","journal-title":"Ann Stat"},{"issue":"1","key":"358_CR13","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/BF02312392","volume":"1","author":"B Fritzke","year":"1994","unstructured":"Fritzke B (1994) Fast learning with incremental RBF networks. Neural Process Lett 1(1): 2\u20135","journal-title":"Neural Process Lett"},{"issue":"2","key":"358_CR14","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1109\/99.388960","volume":"2","author":"AL Graps","year":"1995","unstructured":"Graps AL (1995) An introduction to wavelets. IEEE Comput Sci Eng 2(2): 50\u201361","journal-title":"IEEE Comput Sci Eng"},{"key":"358_CR15","volume-title":"The elements of statistical learning. Data mining, inference, and prediction, chapter boosting and additive trees","author":"T Hastie","year":"2001","unstructured":"Hastie T, Tibshirani R, Friedman J (2001) The elements of statistical learning. Data mining, inference, and prediction, chapter boosting and additive trees. Springer, New York"},{"issue":"11","key":"358_CR16","doi-asserted-by":"crossref","first-page":"2636","DOI":"10.1093\/bioinformatics\/bti402","volume":"21","author":"P Hong","year":"2005","unstructured":"Hong P, Liu XS, Zhou Q, Lu X, Liu JS, Wong WH (2005) A boosting approach for motif modeling using chip-chip data. Bioinformatics 21(11): 2636\u20132643","journal-title":"Bioinformatics"},{"issue":"2","key":"358_CR17","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s10115-007-0097-z","volume":"15","author":"S Kadiyala","year":"2008","unstructured":"Kadiyala S, Shiri N (2008) A compact multi-resolution index for variable length queries in time series databases. Knowl Inf Syst 15(2): 131\u2013147","journal-title":"Knowl Inf Syst"},{"key":"358_CR18","doi-asserted-by":"crossref","unstructured":"Krishnaraj Y, Reddy CK (2008) Boosting methods for protein fold recognition: an empirical comparison. In: IEEE International Conference on Bioinformatics and Biomedicine. pp 393\u2013396","DOI":"10.1109\/BIBM.2008.83"},{"issue":"12","key":"358_CR19","doi-asserted-by":"crossref","first-page":"1396","DOI":"10.1109\/34.895974","volume":"22","author":"Y Leung","year":"2000","unstructured":"Leung Y, Zhang J, Xu Z (2000) Clustering by scale-space filtering. IEEE Trans Pattern Anal Mach Intell 22(12): 1396\u20131410","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"358_CR20","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-6465-9","volume-title":"Scale-space theory in computer vision","author":"T Lindeberg","year":"1994","unstructured":"Lindeberg T (1994) Scale-space theory in computer vision. Kluwer Academic Publishers, Dordrecht"},{"key":"358_CR21","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/34.192463","volume":"11","author":"S Mallat","year":"1989","unstructured":"Mallat S (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11: 674\u2013693","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"358_CR22","unstructured":"National Institute of Standards Information Technology Laboratory and Technology (NIST). Nist strd (statistics reference datasets). http:\/\/www.itl.nist.gov\/div898\/strd\/"},{"issue":"2","key":"358_CR23","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s10115-008-0155-1","volume":"19","author":"D Park","year":"2009","unstructured":"Park D (2009) Multiresolution-based bilinear recurrent neural network. Knowl Inf Syst 19(2): 235\u2013248","journal-title":"Knowl Inf Syst"},{"key":"358_CR24","unstructured":"Park J-H, Reddy CK (2007) Scale-space based boosting for weak regressors. In: Proceedings of European Conference on Machine Learning, (ECML \u201907). Warsaw, Poland, pp 666\u2013673"},{"issue":"3","key":"358_CR25","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/s10115-007-0093-3","volume":"14","author":"C Preisach","year":"2008","unstructured":"Preisach C, Schmidt-Thieme L (2008) Ensembles of relational classifiers. Knowl Inf Syst 14(3): 249\u2013272","journal-title":"Knowl Inf Syst"},{"key":"358_CR26","doi-asserted-by":"crossref","unstructured":"Reddy CK, Park J-H (2008) Scale-space kernels for additive modeling. In: Joint IAPR international workshop on structural syntactic and statistical pattern recognition (SSPR & SPR). Orlando, USA, p. 714\u2013723","DOI":"10.1007\/978-3-540-89689-0_75"},{"key":"358_CR27","doi-asserted-by":"crossref","unstructured":"Reddy CK, Park J-H (2009) Multi-resolution boosting for classification and regression problems. In: Proceedings of Pacific-Asia conference on knowledge discovery and data mining (PAKDD). Bangkok, Thailand, pp 196\u2013207","DOI":"10.1007\/978-3-642-01307-2_20"},{"issue":"6","key":"358_CR28","doi-asserted-by":"crossref","first-page":"2723","DOI":"10.1214\/009053607000000785","volume":"35","author":"C Rudin","year":"2007","unstructured":"Rudin C, Schapire RE, Daubechies I (2007) Analysis of boosting algorithms using the smooth margin function. Ann Stat 35(6): 2723\u20132768","journal-title":"Ann Stat"},{"key":"358_CR29","doi-asserted-by":"crossref","unstructured":"Schapire R, Singer Y, Singhal A (1998) Boosting and rocchio applied to text filtering. In: Proceedings of ACM SIGIR. pp 215\u2013223","DOI":"10.1145\/290941.290996"},{"issue":"5","key":"358_CR30","doi-asserted-by":"crossref","first-page":"1651","DOI":"10.1214\/aos\/1024691352","volume":"26","author":"RE Schapire","year":"1998","unstructured":"Schapire RE, Freund Y, Bartlett P, Lee WS (1998) Boosting the margin: a new explanation for the effectiveness of voting methods. Ann Stat 26(5): 1651\u20131686","journal-title":"Ann Stat"},{"issue":"3","key":"358_CR31","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1023\/A:1007614523901","volume":"37","author":"RE Schapire","year":"1999","unstructured":"Schapire RE, Singer Y (1999) Improved boosting using confidence-rated predictions. Mach Learn 37(3): 297\u2013336","journal-title":"Mach Learn"},{"key":"358_CR32","doi-asserted-by":"crossref","DOI":"10.1007\/978-94-015-8802-7","volume-title":"Gaussian scale-space theory","author":"J Sporring","year":"1997","unstructured":"Sporring J, Nielsen M, Florack L, Johansen P (1997) Gaussian scale-space theory. Kluwer Academic Publishers, Dordrecht"},{"issue":"1\u20132","key":"358_CR33","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1023\/B:VISI.0000004830.93820.78","volume":"56","author":"K Tieu","year":"2004","unstructured":"Tieu K, Viola PA (2004) Boosting image retrieval. Int J Comput Vis 56(1\u20132): 17\u201336","journal-title":"Int J Comput Vis"},{"issue":"2","key":"358_CR34","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","volume":"57","author":"PA Viola","year":"2004","unstructured":"Viola PA, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57(2): 137\u2013154","journal-title":"Int J Comput Vis"},{"issue":"2","key":"358_CR35","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1023\/A:1007659514849","volume":"40","author":"GI Webb","year":"2000","unstructured":"Webb GI (2000) Multiboosting: a technique for combining boosting and wagging. Mach Learn 40(2): 159\u2013196","journal-title":"Mach Learn"},{"key":"358_CR36","volume-title":"Data mining: practical machine learning tools and techniques, 2nd edn","author":"IH Witten","year":"2005","unstructured":"Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, Los Altos"},{"key":"358_CR37","unstructured":"Zemel RS, Pitassi T (2000) A gradient-based boosting algorithm for regression problems. In: Neural information processing systems. pp 696\u2013702"},{"key":"358_CR38","unstructured":"Zhu J, Rosset S, Zou H, Hastie T (2005) Multi-class adaboost. Technical Report 430, Department of Statistics, University of Michigan"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-010-0358-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-010-0358-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-010-0358-0","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T07:18:48Z","timestamp":1711955928000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-010-0358-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,11,16]]},"references-count":38,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2011,11]]}},"alternative-id":["358"],"URL":"https:\/\/doi.org\/10.1007\/s10115-010-0358-0","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,11,16]]}}}