{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T19:53:24Z","timestamp":1772135604650,"version":"3.50.1"},"reference-count":67,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2012,3,28]],"date-time":"2012-03-28T00:00:00Z","timestamp":1332892800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mach Learn"],"published-print":{"date-parts":[[2012,6]]},"DOI":"10.1007\/s10994-012-5282-y","type":"journal-article","created":{"date-parts":[[2012,3,27]],"date-time":"2012-03-27T13:20:23Z","timestamp":1332854423000},"page":"259-301","source":"Crossref","is-referenced-by-count":34,"title":["Multi-output learning via spectral filtering"],"prefix":"10.1007","volume":"87","author":[{"given":"Luca","family":"Baldassarre","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lorenzo","family":"Rosasco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Annalisa","family":"Barla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessandro","family":"Verri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,3,28]]},"reference":[{"key":"5282_CR1","first-page":"484","volume-title":"Proceedings of the 20th annual conference on learning theory","author":"J. Abernethy","year":"2007","unstructured":"Abernethy, J., Bartlett, P. L., & Rakhlin, A. (2007). Multitask learning with expert advice. In Proceedings of the 20th annual conference on learning theory (pp. 484\u2013498). Berlin: Springer."},{"key":"5282_CR2","first-page":"803","volume":"10","author":"J. Abernethy","year":"2009","unstructured":"Abernethy, J., Bach, F., Evgeniou, T., & Vert, J.-P. (2009). A new approach to collaborative filtering: Operator estimation with spectral regularization. Journal of Machine Learning Research, 10, 803\u2013826.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR3","first-page":"9","volume-title":"Proceedings of the twelfth international conference on artificial intelligence and statistics","author":"M. Alvarez","year":"2009","unstructured":"Alvarez, M., Luengo, D., & Lawrence, N. (2009). Latent force models. In Proceedings of the twelfth international conference on artificial intelligence and statistics (Vol.\u00a05, pp. 9\u201316)."},{"key":"5282_CR4","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/s10994-007-5040-8","volume":"73","author":"A. Argyriou","year":"2008","unstructured":"Argyriou, A., Evgeniou, T., & Pontil, M. (2008a). Convex multi-task feature learning. Machine Learning, 73, 243\u2013272.","journal-title":"Machine Learning"},{"key":"5282_CR5","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/978-3-540-87479-9_23","volume-title":"The European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD)","author":"A. Argyriou","year":"2008","unstructured":"Argyriou, A., Maurer, A., & Pontil, M. (2008b). An algorithm for transfer learning in a heterogeneous environment. In The European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD) (pp. 71\u201385)."},{"key":"5282_CR6","first-page":"83","volume":"4","author":"B. Bakker","year":"2003","unstructured":"Bakker, B., & Heskes, T. (2003). Task clustering and gating for Bayesian multitask learning. Journal of Machine Learning Research, 4, 83\u201399. ISSN 1533-7928.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR7","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1007\/978-3-642-15880-3_10","volume-title":"The European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD)","author":"L. Baldassarre","year":"2010","unstructured":"Baldassarre, L., Rosasco, L., Barla, A., & Verri, A. (2010). Vector field learning via spectral filtering. In The European conference on machine learning and principles and practice of knowledge discovery in databases (ECML PKDD) (pp. 56\u201371)."},{"issue":"1","key":"5282_CR8","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/BF01420984","volume":"12","author":"J. L. Barron","year":"1994","unstructured":"Barron, J. L., Fleet, D. J., & Beauchemin, S. S. (1994). Performance of optical flow techniques. International Journal of Computer Vision, 12(1), 43\u201377.","journal-title":"International Journal of Computer Vision"},{"issue":"1","key":"5282_CR9","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jco.2006.07.001","volume":"23","author":"F. Bauer","year":"2007","unstructured":"Bauer, F., Pereverzev, S., & Rosasco, L. (2007). On regularization algorithms in learning theory. Journal of Complexity, 23(1), 52\u201372. ISSN\u00a00885-064X.","journal-title":"Journal of Complexity"},{"key":"5282_CR10","volume-title":"Pattern recognition and machine learning","author":"C. M. Bishop","year":"2006","unstructured":"Bishop, C. M. (2006). Pattern recognition and machine learning. New York: Springer."},{"key":"5282_CR11","volume-title":"Advances in neural information processing systems (NIPS)","author":"E. V. Bonilla","year":"2007","unstructured":"Bonilla, E. V., Chai, K. M., & Williams, C. (2007). Multi-task Gaussian process prediction. In Advances in neural information processing systems (NIPS). Rostrevor: Curran Associates, Inc."},{"key":"5282_CR12","first-page":"499","volume":"2","author":"O. Bousquet","year":"2002","unstructured":"Bousquet, O., & Elisseeff, A. (2002). Stability and generalization. Journal of Machine Learning Research, 2, 499\u2013526. ISSN 1533\u20137928.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR13","volume-title":"Advances in neural information processing systems (NIPS).","author":"P. Boyle","year":"2005","unstructured":"Boyle, P., & Frean, M. (2005). Dependent Gaussian processes. In Advances in neural information processing systems (NIPS). Cambridge: MIT Press."},{"issue":"1","key":"5282_CR14","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1111\/1467-9868.00054","volume":"59","author":"L. Breiman","year":"1997","unstructured":"Breiman, L., & Friedman, J. H. (1997). Predicting multivariate responses in multiple linear regression. Journal of the Royal Statistical Society, 59(1), 3\u201354.","journal-title":"Journal of the Royal Statistical Society"},{"key":"5282_CR15","first-page":"1562","volume-title":"International joint conference on neural networks","author":"M. Brudnak","year":"2006","unstructured":"Brudnak, M. (2006). Vector-valued support vector regression. In International joint conference on neural networks, 16\u201321 July 2006 (pp. 1562\u20131569)."},{"key":"5282_CR16","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1198\/016214503000125","volume":"98","author":"P. B\u00fchlmann","year":"2002","unstructured":"B\u00fchlmann, P., & Yu, B. (2002). Boosting with the l 2-loss: Regression and classification. Journal of the American Statistical Association, 98, 324\u2013340.","journal-title":"Journal of the American Statistical Association"},{"key":"5282_CR17","unstructured":"Caponnetto, A. (2006). Optimal rates for regularization operators in learning theory (Technical report). CBCL paper 264\/CSAIL-TR 2006-062, MIT."},{"key":"5282_CR18","unstructured":"Caponnetto, A., & De Vito, E. (2005). Risk bounds for regularized least-squares algorithm with operator-valued kernels (Technical report). CBCL paper 249\/CSAIL-TR-2005-031, MIT."},{"issue":"3","key":"5282_CR19","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s10208-006-0196-8","volume":"7","author":"A. Caponnetto","year":"2007","unstructured":"Caponnetto, A., & De Vito, E. (2007). Optimal rates for regularized least-squares algorithm. Foundations of Computational Mathematics, 7(3), 331\u2013368.","journal-title":"Foundations of Computational Mathematics"},{"key":"5282_CR20","first-page":"1615","volume":"9","author":"A. Caponnetto","year":"2008","unstructured":"Caponnetto, A., Micchelli, C. A., Pontil, M., & Ying, Y. (2008). Universal kernels for multi-task learning. Journal of Machine Learning Research, 9, 1615\u20131646. ISSN 1533-7928.","journal-title":"Journal of Machine Learning Research"},{"issue":"4","key":"5282_CR21","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1142\/S0219530506000838","volume":"4","author":"C. Carmeli","year":"2006","unstructured":"Carmeli, C., De Vito, E., & Toigo, A. (2006). Vector valued reproducing kernel Hilbert spaces of integrable functions and Mercer theorem. Analysis and Applications, 4(4), 377\u2013408.","journal-title":"Analysis and Applications"},{"key":"5282_CR22","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1023\/A:1007379606734","volume":"28","author":"R. Caruana","year":"1997","unstructured":"Caruana, R. (1997). Multitask learning. Machine Learning, 28, 41\u201375.","journal-title":"Machine Learning"},{"key":"5282_CR23","volume-title":"Advances in neural information processing systems (NIPS)","author":"K. M. A. Chai","year":"2009","unstructured":"Chai, K. M. A., Williams, C. K. I., Klanke, S., & Vijayakumar, S. (2009). Multi-task Gaussian process learning of robot inverse dynamics. In Advances in neural information processing systems (NIPS). Rostrevor: Curran Associates, Inc."},{"key":"5282_CR24","first-page":"883","volume":"6","author":"E. Vito De","year":"2005","unstructured":"De Vito, E., Rosasco, L., Caponnetto, A., De Giovannini, U., & Odone, F. (2005). Learning from examples as an inverse problem. Journal of Machine Learning Research, 6, 883\u2013904.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR25","unstructured":"De Vito, E., Pereverzev, S., & Rosasco, L. (2008). Adaptive kernel methods via the balancing principle (Technical Report). CBCL paper 275\/CSAIL-TR 2008-062, MIT."},{"key":"5282_CR26","series-title":"Applications of mathematics","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4612-0711-5","volume-title":"A probabilistic theory of pattern recognition","author":"L. Devroye","year":"1996","unstructured":"Devroye, L., Gy\u00f6rfi, L., & Lugosi, G. (1996). Applications of mathematics: Vol. 31. A probabilistic theory of pattern recognition. New York: Springer."},{"key":"5282_CR27","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1613\/jair.105","volume":"2","author":"T. G. Dietterich","year":"1995","unstructured":"Dietterich, T. G., & Bakiri, G. (1995). Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research, 2, 263\u2013286.","journal-title":"Journal of Artificial Intelligence Research"},{"issue":"2","key":"5282_CR28","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1214\/009053604000000067","volume":"32","author":"B. Efron","year":"2004","unstructured":"Efron, B., Hastie, T., Johnstone, I., & Tibshirani, R. (2004). Least angle regression. Annals of Statistics, 32(2), 407\u2013451.","journal-title":"Annals of Statistics"},{"key":"5282_CR29","series-title":"Mathematics and its applications","doi-asserted-by":"crossref","DOI":"10.1007\/978-94-009-1740-8","volume-title":"Regularization of inverse problems","author":"H. W. Engl","year":"1996","unstructured":"Engl, H. W., Hanke, M., & Neubauer, A. (1996). Mathematics and its applications: Vol.\u00a0375. Regularization of inverse problems. Dordrecht: Kluwer Academic."},{"key":"5282_CR30","first-page":"615","volume":"6","author":"T. Evgeniou","year":"2005","unstructured":"Evgeniou, T., Micchelli, C. A., & Pontil, M. (2005). Learning multiple tasks with kernel methods. Journal of Machine Learning Research, 6, 615\u2013637. ISSN 1533-7928.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR31","unstructured":"Fuselier, E. J. Jr. (2006). Refined error estimates for matrix-valued radial basis functions. PhD thesis, Texas A&M University."},{"key":"5282_CR32","unstructured":"Griffin, G., Holub, A., & Perona, P. (2007). Caltech-256 object category dataset (Technical Report 7694). California Institute of Technology."},{"key":"5282_CR33","volume-title":"Advances in neural information processing systems (NIPS)","author":"L. Gunter","year":"2006","unstructured":"Gunter, L., & Zhu, J. (2006). Computing the solution path for the regularized support vector regression. In Advances in neural information processing systems (NIPS) (pp.\u00a0483\u2013490). Cambridge: MIT Press."},{"key":"5282_CR34","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-21606-5","volume-title":"The elements of statistical learning","author":"T. Hastie","year":"2001","unstructured":"Hastie, T., Tibshirani, R., & Friedman, J. (2001). The elements of statistical learning. New York: Springer."},{"key":"5282_CR35","first-page":"1391","volume":"5","author":"T. Hastie","year":"2004","unstructured":"Hastie, T., Saharon, R., Tibshirani, R., & Zhu, J. (2004). The entire regularization path for the support vector machine. Journal of Machine Learning Research, 5, 1391\u20131415.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR36","first-page":"617","volume-title":"Advances in neural information processing systems (NIPS)","author":"S. Haufe","year":"2009","unstructured":"Haufe, S., Nikulin, V. V., Ziehe, A., M\u00fcller, K. R., & Nolte, G. (2009). Estimating vector fields using sparse basis field expansions. In Advances in neural information processing systems (NIPS) (pp. 617\u2013624)."},{"key":"5282_CR37","unstructured":"Hein, M., & Bousquet, O. (2004) Kernels, associated structures and generalizations (Technical Report 127). Max Planck Institute for Biological Cybernetics, July 2004."},{"key":"5282_CR38","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/0047-259X(75)90042-1","volume":"5","author":"A. J. Izenman","year":"1975","unstructured":"Izenman, A. J. (1975). Reduced-rank regression for the multivariate linear model. Journal of Multivariate Analysis, 5, 248\u2013264.","journal-title":"Journal of Multivariate Analysis"},{"key":"5282_CR39","volume-title":"Advances in neural information processing systems (NIPS)","author":"L. Jacob","year":"2008","unstructured":"Jacob, L., Bach, F., & Vert, J. P. (2008). Clustered multi-task learning: A convex formulation. In Advances in neural information processing systems (NIPS). Rostrevor: Curran Associates, Inc."},{"issue":"465","key":"5282_CR40","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1198\/016214504000000098","volume":"99","author":"Y. Lee","year":"2004","unstructured":"Lee, Y., Lin, Y., & Wahba, G. (2004). Multicategory support vector machines: Theory and application to the classification of microarray data and satellite radiance data. Journal of the American Statistical Association, 99(465), 67\u201382.","journal-title":"Journal of the American Statistical Association"},{"issue":"7","key":"5282_CR41","doi-asserted-by":"crossref","first-page":"1873","DOI":"10.1162\/neco.2008.05-07-517","volume":"20","author":"L. Lo Gerfo","year":"2008","unstructured":"Lo Gerfo, L., Rosasco, L., Odone, F., De Vito, E., & Verri, A. (2008). Spectral algorithms for supervised learning. Neural Computation, 20(7), 1873\u20131897.","journal-title":"Neural Computation"},{"issue":"1","key":"5282_CR42","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/s11075-004-3641-x","volume":"39","author":"S. Lowitzsch","year":"2005","unstructured":"Lowitzsch, S. (2005). A density theorem for matrix-valued radial basis functions. Numerical Algorithms, 39(1), 253\u2013256.","journal-title":"Numerical Algorithms"},{"key":"5282_CR43","unstructured":"Mac\u00eado, I., & Castro, R. (2008). Learning divergence-free and curl-free vector fields with matrix-valued kernels (Technical report). Instituto Nacional de Matematica Pura e Aplicada."},{"issue":"5\u20136","key":"5282_CR44","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1081\/NFA-120014755","volume":"23","author":"P. Math\u00e9","year":"2002","unstructured":"Math\u00e9, P., & Pereverzev, S. V. (2002). Moduli of continuity for operator valued functions. Numerical Functional Analysis and Optimization, 23(5\u20136), 623\u2013631.","journal-title":"Numerical Functional Analysis and Optimization"},{"key":"5282_CR45","volume-title":"Predicting structured data","author":"D. McAllester","year":"2007","unstructured":"McAllester, D. (2007). Generalization bounds and consistency for structured learning. In G. Bakir, T. Hofmann, B. Sch\u00f6lkopf, A. Smola, B. Taskar, & S. V. N. Vishwanathan (Eds.), Predicting structured data. Cambridge: MIT Press."},{"key":"5282_CR46","volume-title":"Advances in neural information processing systems (NIPS)","author":"C. A. Micchelli","year":"2004","unstructured":"Micchelli, C. A., & Pontil, M. (2004). Kernels for multi-task learning. In Advances in neural information processing systems (NIPS). New York: MIT Press."},{"key":"5282_CR47","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1162\/0899766052530802","volume":"17","author":"C. A. Micchelli","year":"2005","unstructured":"Micchelli, C. A., & Pontil, M. (2005). On learning vector-valued functions. Neural Computation, 17, 177\u2013204.","journal-title":"Neural Computation"},{"key":"5282_CR48","volume-title":"OPT 2008 optimization for machine learning, NIPS 2008 workshop","author":"S. Mosci","year":"2008","unstructured":"Mosci, S., Santoro, M., Verri, A., Villa, S., & Rosasco, L. (2008). Simple algorithms to solve sparsity based regularization via Fenchel duality. In OPT 2008 optimization for machine learning, NIPS 2008 workshop."},{"issue":"6","key":"5282_CR49","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1007\/BF00198755","volume":"67","author":"F. A. Mussa-Ivaldi","year":"1992","unstructured":"Mussa-Ivaldi, F. A. (1992). From basis functions to basis fields: Vector field approximation from sparse data. Biological Cybernetics, 67(6), 479\u2013489.","journal-title":"Biological Cybernetics"},{"issue":"208","key":"5282_CR50","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1090\/S0025-5718-1994-1254147-6","volume":"63","author":"F. J. Narcowich","year":"1994","unstructured":"Narcowich, F. J., & Ward, J. D. (1994). Generalized Hermite interpolation via matrix-valued conditionally positive definite functions. Mathematics of Computation, 63(208), 661\u2013687.","journal-title":"Mathematics of Computation"},{"key":"5282_CR51","unstructured":"Obozinski, G., Taskar, B., & Jordan, M. I. (2007). Multi-task feature selection (Technical report). Department of Statistics, UC Berkeley."},{"key":"5282_CR52","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1038\/nature02341","volume":"428","author":"T. Poggio","year":"2004","unstructured":"Poggio, T., Rifkin, R., Mukherjee, S., & Niyogi, P. (2004). General conditions for predictivity in learning theory. Nature, 428, 419\u2013422.","journal-title":"Nature"},{"key":"5282_CR53","first-page":"101","volume":"5","author":"R. Rifkin","year":"2004","unstructured":"Rifkin, R., & Klautau, A. (2004). In defense of one-vs-all classification. Journal of Machine Learning Research, 5, 101\u2013141. ISSN 1533-7928.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR54","unstructured":"Rifkin, R., & Lippert, R. A. (2007). Notes on regularized least squares (Technical Report). CBCL Paper 268, MIT."},{"issue":"1","key":"5282_CR55","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/BF02786620","volume":"13","author":"L. Schwartz","year":"1964","unstructured":"Schwartz, L. (1964). Sous-espaces hilbertiens d\u2019espaces vectoriels topologiques et noyaux associ\u00e9s (noyaux reproduisants). Journal d\u2019analyse math\u00e9matique, 13(1), 115\u2013256.","journal-title":"Journal d\u2019analyse math\u00e9matique"},{"key":"5282_CR56","unstructured":"Sheldon, D. (2008). Graphical multi-task learning (Technical report). Cornell University."},{"key":"5282_CR57","volume-title":"Advances in neural information processing systems (NIPS).","author":"A. J. Smola","year":"1998","unstructured":"Smola, A. J., Chaussee, R., & Sch\u00f6lkopf, B. (1998). From regularization operators to support vector kernels. In Advances in neural information processing systems (NIPS). Cambridge: MIT Press."},{"key":"5282_CR58","series-title":"Springer series in statistics","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4612-1494-6","volume-title":"Interpolation of spatial data","author":"M. L. Stein","year":"1999","unstructured":"Stein, M. L. (1999). Springer series in statistics. Interpolation of spatial data. New York: Springer."},{"key":"5282_CR59","first-page":"67","volume":"2","author":"I. Steinwart","year":"2002","unstructured":"Steinwart, I. (2002). On the influence of the kernel on the consistency of support vector machines. Journal of Machine Learning Research, 2, 67\u201393. ISSN 1533-7928.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR60","unstructured":"Szedmak, S., Shawe-Taylor, J., & Isis Group (2005). Learning via linear operators: Maximum margin regression (Technical report). In Proceedings of 2001 IEEE international conference on data mining."},{"key":"5282_CR61","first-page":"143","volume-title":"Proceedings of the 18th annual conference on learning theory","author":"A. Tewari","year":"2005","unstructured":"Tewari, A., & Bartlett, P. L. (2005). On the consistency of multiclass classification methods. In Proceedings of the 18th annual conference on learning theory (Vol.\u00a03559, pp. 143\u2013157). Berlin: Springer."},{"issue":"2","key":"5282_CR62","first-page":"1453","volume":"6","author":"I. Tsochantaridis","year":"2005","unstructured":"Tsochantaridis, I., Joachims, T., Hofmann, T., & Altun, Y. (2005). Large margin methods for structured and interdependent output variables. Journal of Machine Learning Research, 6(2), 1453\u20131484.","journal-title":"Journal of Machine Learning Research"},{"key":"5282_CR63","doi-asserted-by":"crossref","first-page":"27","DOI":"10.2307\/3314667","volume":"8","author":"A. Merwe van\u00a0der","year":"1980","unstructured":"van\u00a0der Merwe, A., & Zidek, J. V. (1980). Multivariate regression analysis and canonical variates. Canadian Journal of Statistics, 8, 27\u201339.","journal-title":"Canadian Journal of Statistics"},{"key":"5282_CR64","first-page":"1820","volume-title":"13th IFAC symposium on system identification, SYSID","author":"E. Vazquez","year":"2003","unstructured":"Vazquez, E., & Walter, E. (2003). Multi output support vector regression. In 13th IFAC symposium on system identification, SYSID, Rotterdam, August 2003 (pp.\u00a01820\u20131825). New York: IFAC."},{"issue":"10","key":"5282_CR65","doi-asserted-by":"crossref","first-page":"1753","DOI":"10.1109\/TNN.2008.2002077","volume":"19","author":"G. Wang","year":"2008","unstructured":"Wang, G., Yeung, D. Y., & Lochovsky, F. H. (2008). A new solution path algorithm in support vector regression. IEEE Transactions on Neural Networks, 19(10), 1753\u20131767.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"5282_CR66","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1137\/0905052","volume":"5","author":"S. Wold","year":"1984","unstructured":"Wold, S., Ruhe, H., Wold, H., & Dunn, W. J. III (1984). The collinearity problem in linear regression. The partial least squares (pls) approach to generalizes inverses. SIAM Journal of Scientific and Statistical Computations, 5, 735\u2013743.","journal-title":"SIAM Journal of Scientific and Statistical Computations"},{"key":"5282_CR67","first-page":"1225","volume":"5","author":"T. Zhang","year":"2004","unstructured":"Zhang, T. (2004). Statistical analysis of some multi-category large margin classification methods. Journal of Machine Learning Research, 5, 1225\u20131251.","journal-title":"Journal of Machine Learning Research"}],"container-title":["Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-012-5282-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10994-012-5282-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10994-012-5282-y","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,26]],"date-time":"2019-06-26T04:25:46Z","timestamp":1561523146000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10994-012-5282-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,3,28]]},"references-count":67,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2012,6]]}},"alternative-id":["5282"],"URL":"https:\/\/doi.org\/10.1007\/s10994-012-5282-y","relation":{},"ISSN":["0885-6125","1573-0565"],"issn-type":[{"value":"0885-6125","type":"print"},{"value":"1573-0565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,3,28]]}}}