{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T14:11:36Z","timestamp":1761401496670,"version":"3.37.3"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2010,2,17]],"date-time":"2010-02-17T00:00:00Z","timestamp":1266364800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nat Comput"],"published-print":{"date-parts":[[2011,6]]},"DOI":"10.1007\/s11047-010-9182-4","type":"journal-article","created":{"date-parts":[[2010,2,16]],"date-time":"2010-02-16T15:46:40Z","timestamp":1266335200000},"page":"921-945","source":"Crossref","is-referenced-by-count":7,"title":["Electrostatic field framework for supervised and semi-supervised learning from incomplete data"],"prefix":"10.1007","volume":"10","author":[{"given":"Marcin","family":"Budka","sequence":"first","affiliation":[]},{"given":"Bogdan","family":"Gabrys","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,2,17]]},"reference":[{"issue":"1","key":"9182_CR1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1145\/373626.373638","volume":"30","author":"C Aggarwal","year":"2001","unstructured":"Aggarwal C (2001) Re-designing distance functions and distance-based applications for high dimensional data. ACM SIGMOD Rec 30(1):13\u201318","journal-title":"ACM SIGMOD Rec"},{"key":"9182_CR2","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1007\/3-540-44503-X_27","volume":"2001","author":"C Aggarwal","year":"2001","unstructured":"Aggarwal C, Hinneburg A, Keim D (2001) On the surprising behavior of distance metrics in high dimensional space. Lect Notes Comput Sci 2001:420\u2013435","journal-title":"Lect Notes Comput Sci"},{"key":"9182_CR3","unstructured":"Asuncion A, Newman D (2007) UCI machine learning repository"},{"key":"9182_CR4","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/3-540-49257-7_15","volume":"1540","author":"K Beyer","year":"1999","unstructured":"Beyer K, Goldstein J, Ramakrishnan R, Shaft U (1999) When is \u201cnearest neighbor\u201d meaningful. Lect Notes Comput Sci 1540:217\u2013235","journal-title":"Lect Notes Comput Sci"},{"key":"9182_CR5","doi-asserted-by":"crossref","unstructured":"Blum A, Mitchell T (1998) Combining labeled and unlabeled data with co-training. In: Proceedings of the eleventh annual conference on computational learning theory. ACM, New York, NY, USA, pp 92\u2013100","DOI":"10.1145\/279943.279962"},{"key":"9182_CR6","doi-asserted-by":"crossref","unstructured":"Budka M, Gabrys B (2009) Electrostatic field classifier for deficient data. In: Computer recognition systems 3: Proceedings of 6th international conference on computer recognition systems cores 09. Springer, pp 311\u2013318","DOI":"10.1007\/978-3-540-93905-4_37"},{"key":"9182_CR7","unstructured":"Chuang I, Nielsen M (2000) Quantum information. Cambridge University Press"},{"key":"9182_CR8","unstructured":"Dara R, Kremer S, Stacey D (2002) Clustering unlabeled data with SOMs improves classification of labeled real-world data. In: Neural networks, 2002. IJCNN\u201902. Proceedings of the 2002 international joint conference on, vol 3, pp 2237\u20132242"},{"issue":"1","key":"9182_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"A Dempster","year":"1977","unstructured":"Dempster A, Laird N, Rubin D (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B (Methodol) 39(1):1\u201338","journal-title":"J R Stat Soc Ser B (Methodol)"},{"key":"9182_CR10","unstructured":"Duin R, Juszczak P, Paclik P, Pekalska E, de Ridder D, Tax D, Verzakov S (2007) Pr-tools 4.1, a matlab toolbox for pattern recognition. http:\/\/prtools.org"},{"key":"9182_CR11","unstructured":"Francois D, Wertz V, Verleysen M (2005) Non-Euclidean metrics for similarity search in noisy datasets. In: Proceedings of the European symposium on artificial neural networks, pp 339\u2013334"},{"issue":"3","key":"9182_CR12","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/S0888-613X(02)00070-1","volume":"30","author":"B Gabrys","year":"2002","unstructured":"Gabrys B (2002) Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems. Int J Approx Reason 30(3):149\u2013179","journal-title":"Int J Approx Reason"},{"issue":"3","key":"9182_CR13","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.ijar.2003.08.005","volume":"35","author":"B Gabrys","year":"2004","unstructured":"Gabrys B, Petrakieva L (2004) Combining labelled and unlabelled data in the design of pattern classification systems. Int J Approx Reason 35(3):251\u2013273","journal-title":"Int J Approx Reason"},{"key":"9182_CR14","first-page":"120","volume":"6","author":"Z Ghahramani","year":"1994","unstructured":"Ghahramani Z, Jordan M, Cowan J, Tesauro G, Alspector J (1994) Supervised learning from incomplete data via an EM approach. Adv Neural Inf Process Syst 6:120\u2013127","journal-title":"Adv Neural Inf Process Syst"},{"key":"9182_CR16","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1002\/0471264385.wei0204","volume":"2","author":"J Graham","year":"2003","unstructured":"Graham J, Cumsille P, Elek-Fisk E (2003) Methods for handling missing data. Handb Psychol 2:87\u2013114","journal-title":"Handb Psychol"},{"key":"9182_CR17","doi-asserted-by":"crossref","unstructured":"Hakkoymaz H, Chatzimilioudis G, Gunopulos D, Mannila H (2009) Applying electromagnetic field theory concepts to clustering with constraints. In: Proceedings of the European conference on machine learning and knowledge discovery in databases: part I. Springer, p 500","DOI":"10.1007\/978-3-642-04180-8_49"},{"issue":"6","key":"9182_CR18","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1109\/97.923043","volume":"8","author":"K Hild","year":"2001","unstructured":"Hild K, Erdogmus D, Principe J (2001) Blind source separation using Renyi\u2019s mutual information. IEEE Signal Process Lett 8(6):174\u2013176","journal-title":"IEEE Signal Process Lett"},{"key":"9182_CR19","unstructured":"Hochreiter S, Mozer M (2001) Coulomb classifiers: reinterpreting SVMs as electrostatic systems. Technical report CU-CS-921-01. Department of Computer Science, University of Colorado, Boulder"},{"key":"9182_CR20","first-page":"545","volume":"15","author":"S Hochreiter","year":"2003","unstructured":"Hochreiter S, Mozer M, Obermayer K (2003) Coulomb classifiers: generalizing support vector machines via an analogy to electrostatic systems. Adv Neural Inf Process Syst 15:545\u2013552","journal-title":"Adv Neural Inf Process Syst"},{"issue":"1","key":"9182_CR21","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s11265-006-9771-8","volume":"45","author":"R Jenssen","year":"2006","unstructured":"Jenssen R, Eltoft T, Erdogmus D, Principe J (2006) Some equivalences between kernel methods and information theoretic methods. J VLSI Signal Process 45(1):49\u201365","journal-title":"J VLSI Signal Process"},{"key":"9182_CR22","unstructured":"Kothari R, Jain V (2002) Learning from labeled and unlabeled data. In: Neural networks, 2002. IJCNN\u201902. Proceedings of the 2002 international joint conference on, vol 3"},{"key":"9182_CR23","doi-asserted-by":"crossref","unstructured":"Kuncheva L (2000) Fuzzy classifier design. Physica Verlag","DOI":"10.1007\/978-3-7908-1850-5"},{"issue":"1","key":"9182_CR24","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1103\/PhysRevA.57.120","volume":"57","author":"D Loss","year":"1998","unstructured":"Loss D, DiVincenzo D (1998) Quantum computation with quantum dots. Phys Rev A 57(1):120\u2013126","journal-title":"Phys Rev A"},{"key":"9182_CR25","unstructured":"Madow W, Olkin I (1983) Incomplete data in sample surveys, vol 3, Proceedings of the symposium. Academic Press, New York"},{"key":"9182_CR26","unstructured":"Mitchell T (1999) The role of unlabeled data in supervised learning. In: Proceedings of the sixth international colloquium on cognitive science"},{"key":"9182_CR27","unstructured":"Nigam K, Ghani R (2000) Understanding the behavior of co-training. In: Proceedings of KDD-2000 workshop on text mining"},{"key":"9182_CR28","doi-asserted-by":"crossref","unstructured":"Outhwaite W, Turner SP (2007) Handbook of social science methodology. SAGE Publications Ltd","DOI":"10.4135\/9781848607958"},{"issue":"5","key":"9182_CR29","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1109\/3477.623232","volume":"27","author":"W Pedrycz","year":"1997","unstructured":"Pedrycz W, Waletzky J (1997) Fuzzy clustering with partial supervision. IEEE Trans Syst Man Cybern B 27(5):787\u2013795","journal-title":"IEEE Trans Syst Man Cybern B"},{"key":"9182_CR30","unstructured":"Principe J, Xu D, Fisher J (2000a) Information theoretic learning, chapter 7. Wiley, New York, pp 265\u2013319"},{"issue":"1","key":"9182_CR31","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1023\/A:1008143417156","volume":"26","author":"J Principe","year":"2000","unstructured":"Principe J, Xu D, Zhao Q, Fisher J (2000b) Learning from examples with information theoretic criteria. J VLSI Signal Process 26(1):61\u201377","journal-title":"J VLSI Signal Process"},{"key":"9182_CR32","doi-asserted-by":"crossref","unstructured":"Ripley B (1996) Pattern recognition and neural networks. Cambridge University Press","DOI":"10.1017\/CBO9780511812651"},{"key":"9182_CR33","unstructured":"Roy N, McCallum A (2001) Toward optimal active learning through sampling estimation of error reduction. In: Proceedings of the 18th international conference on machine learning, pp 441\u2013448"},{"issue":"3","key":"9182_CR34","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1093\/biomet\/63.3.581","volume":"63","author":"D Rubin","year":"1976","unstructured":"Rubin D (1976) Inference and missing data. Biometrika 63(3):581\u2013592","journal-title":"Biometrika"},{"key":"9182_CR35","doi-asserted-by":"crossref","unstructured":"Rubin D (1987) Multiple imputation for nonresponse in surveys. Wiley-Interscience","DOI":"10.1002\/9780470316696"},{"issue":"2","key":"9182_CR36","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1007\/s00500-002-0253-z","volume":"8","author":"D Ruta","year":"2003","unstructured":"Ruta D, Gabrys B (2003) Physical field models for pattern classification. Soft Comput 8(2):126\u2013141","journal-title":"Soft Comput"},{"key":"9182_CR37","unstructured":"Ruta D, Gabrys B (2005) Nature inspired learning models. In: Proceedings of the European symposium on nature inspired smart information systems, Albufeira, Portugal"},{"issue":"2","key":"9182_CR38","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1007\/s11047-007-9064-6","volume":"8","author":"D Ruta","year":"2009","unstructured":"Ruta D, Gabrys B (2009) A framework for machine learning based on dynamic physical fields. Nat Comput 8(2):219\u2013237","journal-title":"Nat Comput"},{"key":"9182_CR39","first-page":"399","volume":"98","author":"W Sarle","year":"1998","unstructured":"Sarle W (1998) Prediction with missing inputs. JCIS 98:399\u2013402","journal-title":"JCIS"},{"issue":"2","key":"9182_CR40","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1037\/1082-989X.7.2.147","volume":"7","author":"J Schafer","year":"2002","unstructured":"Schafer J, Graham J (2002) Missing data: our view of the state of the art. Psychol Methods 7(2):147\u2013177","journal-title":"Psychol Methods"},{"issue":"449","key":"9182_CR41","doi-asserted-by":"crossref","first-page":"144","DOI":"10.2307\/2669534","volume":"95","author":"J Schafer","year":"2000","unstructured":"Schafer J, Schenker N (2000) Inference with imputed conditional means. J Am Stat Assoc 95(449):144\u2013154","journal-title":"J Am Stat Assoc"},{"key":"9182_CR50","unstructured":"Sg SG, Goldman S, Zhou Y (2000) Enhancing supervised learning with unlabeled data. Proceedings of the 17th international conference on machine learning, pp 327\u2013334"},{"key":"9182_CR42","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1162\/153244303322753742","volume":"3","author":"K Torkkola","year":"2003","unstructured":"Torkkola K (2003) Feature extraction by non parametric mutual information maximization. J Mach Learn Res 3:1415\u20131438","journal-title":"J Mach Learn Res"},{"key":"9182_CR43","first-page":"128","volume":"6","author":"V Tresp","year":"1994","unstructured":"Tresp V, Ahmad S, Neuneier R (1994) Training neural networks with deficient data. Adv Neural Inf Process Syst 6:128\u2013135","journal-title":"Adv Neural Inf Process Syst"},{"key":"9182_CR44","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1038\/nature03347","volume":"434","author":"P Walther","year":"2005","unstructured":"Walther P, Resch K, Rudolph T, Schenck E, Weinfurter H, Vedral V, Aspelmeyer M, Zeilinger A (2005) Experimental one-way quantum computing. Nature 434:169\u2013176","journal-title":"Nature"},{"key":"9182_CR45","unstructured":"Zurek W (1989) Complexity, entropy and the physics of information. Westview Press"}],"container-title":["Natural Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11047-010-9182-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11047-010-9182-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11047-010-9182-4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T14:41:17Z","timestamp":1739889677000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11047-010-9182-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,2,17]]},"references-count":45,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2011,6]]}},"alternative-id":["9182"],"URL":"https:\/\/doi.org\/10.1007\/s11047-010-9182-4","relation":{},"ISSN":["1567-7818","1572-9796"],"issn-type":[{"type":"print","value":"1567-7818"},{"type":"electronic","value":"1572-9796"}],"subject":[],"published":{"date-parts":[[2010,2,17]]}}}