{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T12:22:07Z","timestamp":1763641327288,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":31,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642041792"},{"type":"electronic","value":"9783642041808"}],"license":[{"start":{"date-parts":[[2009,1,1]],"date-time":"2009-01-01T00:00:00Z","timestamp":1230768000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009]]},"DOI":"10.1007\/978-3-642-04180-8_52","type":"book-chapter","created":{"date-parts":[[2009,8,27]],"date-time":"2009-08-27T08:11:20Z","timestamp":1251360680000},"page":"533-547","source":"Crossref","is-referenced-by-count":12,"title":["Feature Selection by Transfer Learning with Linear Regularized Models"],"prefix":"10.1007","author":[{"given":"Thibault","family":"Helleputte","sequence":"first","affiliation":[]},{"given":"Pierre","family":"Dupont","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"15","key":"52_CR1","doi-asserted-by":"publisher","first-page":"5923","DOI":"10.1073\/pnas.0601231103","volume":"103","author":"L. Ein-Dor","year":"2006","unstructured":"Ein-Dor, L., Zuk, O., Domany, E.: Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. PNAS\u00a0103(15), 5923\u20135928 (2006)","journal-title":"PNAS"},{"key":"52_CR2","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1038\/nbt1206-1471","volume":"24","author":"R. Edgar","year":"2006","unstructured":"Edgar, R., Barrett, T.: Ncbi geo standards and services for microarray data. Nature Biotechnology\u00a024, 1471\u20131472 (2006)","journal-title":"Nature Biotechnology"},{"issue":"suppl-1","key":"52_CR3","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1093\/nar\/gkn889","volume":"37","author":"H. Parkinson","year":"2009","unstructured":"Parkinson, H., Kapushesky, M., Kolesnikov, N., Rustici, G., Shojatalab, M., Abeygunawardena, N., Berube, H., Dylag, M., Emam, I., Farne, A., Holloway, E., Lukk, M., Malone, J., Mani, R., Pilicheva, E., Rayner, T.F., Rezwan, F., Sharma, A., Williams, E., Bradley, X.Z., Adamusiak, T., Brandizi, M., Burdett, T., Coulson, R., Krestyaninova, M., Kurnosov, P., Maguire, E., Neogi, S.G., Rocca-Serra, P., Sansone, S.-A., Sklyar, N., Zhao, M., Sarkans, U., Brazma, A.: ArrayExpress update\u2013from an archive of functional genomics experiments to the atlas of gene expression. Nucl. Acids Res.\u00a037(suppl-1), D868\u2013D872 (2009)","journal-title":"Nucl. Acids Res."},{"key":"52_CR4","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/s10994-008-5087-1","volume":"73","author":"D.L. Silver","year":"2008","unstructured":"Silver, D.L., Bennett, K.P.: Guest editor\u2019s introduction: special issue on inductive transfer learning. Machine Learning\u00a073, 215\u2013220 (2008)","journal-title":"Machine Learning"},{"key":"52_CR5","unstructured":"Pan, S.J., Yang, Q.: A survey on transfer learning. Technical Report HKUST-CS08-08, Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China (November 2008)"},{"volume-title":"Semi-Supervised Learning","year":"2006","key":"52_CR6","unstructured":"Chapelle, O., Sch\u00f6lkopf, B., Zien, A. (eds.): Semi-Supervised Learning. MIT Press, Cambridge (2006)"},{"key":"52_CR7","doi-asserted-by":"crossref","unstructured":"Argyriou, A., Evgeniou, T., Pontil, M.: Multi-task feature learning. In: NIPS, pp. 41\u201348 (2006)","DOI":"10.2139\/ssrn.1031158"},{"key":"52_CR8","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1613\/jair.1872","volume":"26","author":"H. Daum\u00e9 III","year":"2007","unstructured":"Daum\u00e9 III, H., Marcu, D.: Domain adaptation for statistical classifiers. Journal of Artificial Intelligence Research\u00a026, 101\u2013126 (2007)","journal-title":"Journal of Artificial Intelligence Research"},{"key":"52_CR9","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1007\/978-3-540-87481-2_36","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Z. Wang","year":"2008","unstructured":"Wang, Z., Song, Y., Zhang, C.: Transferred dimensionality reduction. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008, Part II. LNCS (LNAI), vol.\u00a05212, pp. 550\u2013565. Springer, Heidelberg (2008)"},{"key":"52_CR10","doi-asserted-by":"crossref","unstructured":"Liao, X., Xue, Y., Carin, L.: Logistic regression with an auxiliray data source. In: Proceedings of the 22nd International Conference on Machine Learning, Bonn, Germany, pp. 505\u2013512 (2005)","DOI":"10.1145\/1102351.1102415"},{"key":"52_CR11","first-page":"601","volume-title":"Proceedings of the 19th Annual Conference on Neural Information Processing Systems","author":"J. Huang","year":"2007","unstructured":"Huang, J., Smola, A., Gretton, A., Borgwardt, K., Sch\u00f6lkopf, B.: Correcting sample selection bias by unlabeled data. In: Proceedings of the 19th Annual Conference on Neural Information Processing Systems, pp. 601\u2013608. MIT Press, Cambridge (2007)"},{"key":"52_CR12","doi-asserted-by":"crossref","unstructured":"Dai, W., Yang, Q., Xue, G., Yu, Y.: Selft-thaught clustering. In: Proceedings of the 25th International Conference of Machine Learning, pp. 200\u2013207 (2008)","DOI":"10.1145\/1390156.1390182"},{"key":"52_CR13","doi-asserted-by":"crossref","unstructured":"Evgeniou, T., Pontil, M.: Regularized multi-task learning. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 109\u2013117 (2004)","DOI":"10.1145\/1014052.1014067"},{"key":"52_CR14","first-page":"65","volume-title":"Proceedings of the 21st International Conference on Machine Learning","author":"N. Lawrence","year":"2004","unstructured":"Lawrence, N., Platt, C.: Learning to learn with the informative vector machine. In: Proceedings of the 21st International Conference on Machine Learning, p. 65. ACM, New York (2004)"},{"key":"52_CR15","doi-asserted-by":"crossref","unstructured":"Blitzer, J., McDonald, R., Pereira, F.: Domain adaptation with structural correspondence learning. In: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, Sydney, Australia, July 2006, pp. 120\u2013128. Association for Computational Linguistics (2006)","DOI":"10.3115\/1610075.1610094"},{"key":"52_CR16","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1007\/11564096_64","volume-title":"Machine Learning: ECML 2005","author":"I. Mierswa","year":"2005","unstructured":"Mierswa, I., Wurst, M.: Efficient case based feature construction. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol.\u00a03720, pp. 641\u2013648. Springer, Heidelberg (2005)"},{"key":"52_CR17","first-page":"1157","volume":"3","author":"I. Guyon","year":"2003","unstructured":"Guyon, I., Elisseef, A.: An introduction to variable and feature selection. Journal of Machine Learning Research\u00a03, 1157\u20131182 (2003)","journal-title":"Journal of Machine Learning Research"},{"issue":"19","key":"52_CR18","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1093\/bioinformatics\/btm344","volume":"23","author":"Y. Saeys","year":"2007","unstructured":"Saeys, Y., Inza, I., Larranaga, P.: A review of feature selection techniques in bioinformatics. bioinformatics\u00a023(19), 2507\u20132517 (2007)","journal-title":"bioinformatics"},{"key":"52_CR19","doi-asserted-by":"crossref","first-page":"299","DOI":"10.7551\/mitpress\/4057.003.0019","volume-title":"Kernel Methods in Computational Biology","author":"B. Krishnapuram","year":"2004","unstructured":"Krishnapuram, B., Carin, L., Hartemink, A.: 14: Gene Expression Analysis: Joint Feature Selection and Classifier Design. In: Kernel Methods in Computational Biology, pp. 299\u2013317. MIT Press, Cambridge (2004)"},{"key":"52_CR20","doi-asserted-by":"crossref","unstructured":"Ein-Dor, L., Kela, I., Getz, G., Givol, D., Domany, E.: Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 21 (2005)","DOI":"10.1093\/bioinformatics\/bth469"},{"key":"52_CR21","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1007\/0-306-47815-3_9","volume-title":"A Practical Approach to Microarray Data Analysis","author":"S. Mukherjee","year":"2003","unstructured":"Mukherjee, S.: 9: Classifying Microarray Data Using Support Vector Machines. In: A Practical Approach to Microarray Data Analysis, pp. 166\u2013185. Springer, Heidelberg (2003)"},{"key":"52_CR22","unstructured":"Weston, J., Mukherjee, S., Chapelle, O., Pontil, M., Poggio, T., Vapnik, V.: Feature selection for SVMs. In: Advances in Neural Information Processing Systems, pp. 668\u2013674 (2000)"},{"key":"52_CR23","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1023\/A:1012450327387","volume":"46","author":"O. Chapelle","year":"2002","unstructured":"Chapelle, O., Vapnik, V., Bousquet, O., Mukherjee, S.: Choosing multiple parameters for support vector machines. Machine Learning\u00a046, 131\u2013159 (2002)","journal-title":"Machine Learning"},{"issue":"1-3","key":"52_CR24","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1023\/A:1012487302797","volume":"46","author":"I. Guyon","year":"2002","unstructured":"Guyon, I., Weston, J., Barnhill, S., Vapnik, V.: Gene selection for cancer classification using support vector machines. Machine Learning\u00a046(1-3), 389\u2013422 (2002)","journal-title":"Machine Learning"},{"key":"52_CR25","first-page":"1439","volume":"3","author":"J. Weston","year":"2003","unstructured":"Weston, J., Elisseef, A., Sch\u00f6lkopf, B., Tipping, M.: Use of the zero-norm with linear models and kernel methods. Journal of Machine Learning Research\u00a03, 1439\u20131461 (2003)","journal-title":"Journal of Machine Learning Research"},{"key":"52_CR26","doi-asserted-by":"crossref","unstructured":"Helleputte, T., Dupont, P.: Partially supervised feature selection with regularized linear models. In: Proceedings of the 26th International Conference on Machine Learning (2009)","DOI":"10.1145\/1553374.1553427"},{"issue":"2","key":"52_CR27","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1016\/S1535-6108(02)00030-2","volume":"1","author":"D. Singh","year":"2002","unstructured":"Singh, D., Febbo, P.G., Ross, K., Jackson, D.G., Manola, J., Ladd, C., Tamayo, P., Renshaw, A.A., D\u2019Amico, A.V., Richie, J.P., Lander, E.S., Loda, M., Kantoff, P.W., Golub, T.R., Sellers, W.R.: Gene expression correlates of clinical prostate cancer behavior. Cancer Cell\u00a01(2), 203\u2013209 (2002)","journal-title":"Cancer Cell"},{"issue":"1","key":"52_CR28","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1186\/1471-2407-7-64","volume":"7","author":"U. Chandran","year":"2007","unstructured":"Chandran, U., Ma, C., Dhir, R., Bisceglia, M., Lyons-Weiler, M., Liang, W., Michalopoulos, G., Becich, M., Monzon, F.: Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process. BMC Cancer\u00a07(1), 64 (2007)","journal-title":"BMC Cancer"},{"issue":"16","key":"52_CR29","first-page":"5974","volume":"61","author":"J.B. Welsh","year":"2001","unstructured":"Welsh, J.B., Sapinoso, L.M., Su, A.I., Kern, S.G., Wang-Rodriguez, J., Moskaluk, C.A., Frierson Jr., F.H., Hampton, G.M.: Analysis of Gene Expression Identifies Candidate Markers and Pharmacological Targets in Prostate Cancer. Cancer Res\u00a061(16), 5974\u20135978 (2001)","journal-title":"Cancer Res"},{"key":"52_CR30","unstructured":"Kuncheva, L.I.: A stability index for feature selection. In: Proceedings of the 25th International Multi-Conference: Artificial Intelligence and Applications, Anaheim, CA, USA, pp. 390\u2013395. ACTA Press (2007)"},{"key":"52_CR31","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1023\/A:1024068626366","volume":"52","author":"C. Nadeau","year":"2003","unstructured":"Nadeau, C., Bengio, Y.: Inference for the generalization error. Machine Learning\u00a052, 239\u2013281 (2003)","journal-title":"Machine Learning"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-04180-8_52","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,16]],"date-time":"2024-03-16T03:46:30Z","timestamp":1710560790000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-04180-8_52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"ISBN":["9783642041792","9783642041808"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-04180-8_52","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2009]]}}}