{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T17:56:55Z","timestamp":1742925415273,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":27,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642352881"},{"type":"electronic","value":"9783642352898"}],"license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"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":[[2012]]},"DOI":"10.1007\/978-3-642-35289-8_6","type":"book-chapter","created":{"date-parts":[[2012,11,14]],"date-time":"2012-11-14T12:03:17Z","timestamp":1352894597000},"page":"69-89","source":"Crossref","is-referenced-by-count":1,"title":["A Simple Trick for Estimating the Weight Decay Parameter"],"prefix":"10.1007","author":[{"given":"Thorsteinn S.","family":"R\u00f6gnvaldsson","sequence":"first","affiliation":[]}],"member":"297","reference":[{"key":"6_CR1","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1162\/neco.1995.7.4.639","volume":"7","author":"Y.S. Abu-Mustafa","year":"1995","unstructured":"Abu-Mustafa, Y.S.: Hints. Neural Computation\u00a07, 639\u2013671 (1995)","journal-title":"Neural Computation"},{"issue":"5","key":"6_CR2","doi-asserted-by":"publisher","first-page":"882","DOI":"10.1109\/72.248466","volume":"4","author":"C.M. Bishop","year":"1993","unstructured":"Bishop, C.M.: Curvature-driven smoothing: A learning algorithm for feedforward networks. IEEE Transactions on Neural Networks\u00a04(5), 882\u2013884 (1993)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"6_CR3","unstructured":"Brace, M.C., Schmidt, J., Hadlin, M.: Comparison of the forecast accuracy of neural networks with other established techniques. In: Proceedings of the First International Form on Application of Neural Networks to Power System, Seattle WA, pp. 31\u201335 (1991)"},{"key":"6_CR4","first-page":"603","volume":"5","author":"W.L. Buntine","year":"1991","unstructured":"Buntine, W.L., Weigend, A.S.: Bayesian back-propagation. Complex Systems\u00a05, 603\u2013643 (1991)","journal-title":"Complex Systems"},{"key":"6_CR5","first-page":"315","volume-title":"The Mathematics of Generalization - The Proceedings of the SFI\/CNLS Workshop on Formal Approaches to Supervised Learning","author":"P. Cheeseman","year":"1995","unstructured":"Cheeseman, P.: On Bayesian model selection. In: The Mathematics of Generalization - The Proceedings of the SFI\/CNLS Workshop on Formal Approaches to Supervised Learning, pp. 315\u2013330. Addison-Wesley, Reading (1995)"},{"key":"6_CR6","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1007\/BF02551274","volume":"2","author":"G. Cybenko","year":"1989","unstructured":"Cybenko, G.: Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals and Systems\u00a02, 304\u2013314 (1989)","journal-title":"Mathematics of Control, Signals and Systems"},{"key":"6_CR7","unstructured":"Engle, R., Clive, F., Granger, W.J., Ramanathan, R., Vahid, F., Werner, M.: Construction of the puget sound forecasting model. EPRI Project # RP2919, Quantitative Economics Research Institute, San Diego, CA (1991)"},{"issue":"1","key":"6_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/neco.1992.4.1.1","volume":"4","author":"S. Geman","year":"1992","unstructured":"Geman, S., Bienenstock, E., Doursat, R.: Neural networks and the bias\/variance dilemma. Neural Computation\u00a04(1), 1\u201358 (1992)","journal-title":"Neural Computation"},{"key":"6_CR9","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1162\/neco.1995.7.2.219","volume":"7","author":"F. Girosi","year":"1995","unstructured":"Girosi, F., Jones, M., Poggio, T.: Regularization theory and neural networks architectures. Neural Computation\u00a07, 219\u2013269 (1995)","journal-title":"Neural Computation"},{"key":"6_CR10","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1109\/NNSP.1994.366061","volume-title":"Proceedings of the IEEE Workshop on Neural Networks for Signal Processing IV","author":"L.K. Hansen","year":"1994","unstructured":"Hansen, L.K., Rasmussen, C.E., Svarer, C., Larsen, J.: Adaptive regularization. In: Vlontzos, J., Hwang, J.-N., Wilson, E. (eds.) Proceedings of the IEEE Workshop on Neural Networks for Signal Processing IV, pp. 78\u201387. IEEE Press, Piscataway (1994)"},{"key":"6_CR11","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1080\/00401706.1970.10488634","volume":"12","author":"A.E. Hoerl","year":"1970","unstructured":"Hoerl, A.E., Kennard, R.W.: Ridge regression: Biased estimation of nonorthogonal problems. Technometrics\u00a012, 55\u201367 (1970)","journal-title":"Technometrics"},{"key":"6_CR12","unstructured":"Ishikawa, M.: A structural learning algorithm with forgetting of link weights. Technical Report TR-90-7, Electrotechnical Laboratory, Information Science Division, 1-1-4 Umezono, Tsukuba, Ibaraki 305, Japan (1990)"},{"key":"6_CR13","volume-title":"The Advanced Theory of Statistics","author":"M.G. Kendall","year":"1972","unstructured":"Kendall, M.G., Stuart, A.: The Advanced Theory of Statistics, 3rd edn. Hafner Publishing Co., New York (1972)","edition":"3"},{"key":"6_CR14","volume-title":"Advances in Neural Information Processing Systems 9","author":"J.E. Moody","year":"1997","unstructured":"Moody, J.E., R\u00f6gnvaldsson, T.S.: Smoothing regularizers for projective basis function networks. In: Advances in Neural Information Processing Systems 9. MIT Press, Cambridge (1997)"},{"key":"6_CR15","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1162\/neco.1992.4.4.473","volume":"4","author":"S. Nowlan","year":"1992","unstructured":"Nowlan, S., Hinton, G.: Simplifying neural networks by soft weight-sharing. Neural Computation\u00a04, 473\u2013493 (1992)","journal-title":"Neural Computation"},{"key":"6_CR16","first-page":"126","volume-title":"Artificial Neural Networks for Speech and Vision","author":"M.P. Perrone","year":"1993","unstructured":"Perrone, M.P., Cooper, L.C.: When networks disagree: Ensemble methods for hybrid neural networks. In: Artificial Neural Networks for Speech and Vision, pp. 126\u2013142. Chapman and Hall, London (1993)"},{"key":"6_CR17","unstructured":"Plaut, D., Nowlan, S., Hinton, G.: Experiments on learning by backpropagation. Technical Report CMU-CS-86-126, Carnegie Mellon University, Pittsburg, PA (1986)"},{"key":"6_CR18","unstructured":"Riedmiller, M., Braun, H.: A direct adaptive method for faster backpropagation learning: The RPROP algorithm. In: Ruspini, H. (ed.) Proc. of the IEEE Intl. Conference on Neural Networks, San Fransisco, California, pp. 586\u2013591 (1993)"},{"key":"6_CR19","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511812651","volume-title":"Pattern Recognition and Neural Networks","author":"B.D. Ripley","year":"1996","unstructured":"Ripley, B.D.: Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge (1996)"},{"issue":"6","key":"6_CR20","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.1080\/00207179508921605","volume":"62","author":"J. Sj\u00f6berg","year":"1995","unstructured":"Sj\u00f6berg, J., Ljung, L.: Overtraining, regularization, and searching for minimum with application to neural nets. Int. J. Control\u00a062(6), 1391\u20131407 (1995)","journal-title":"Int. J. Control"},{"key":"6_CR21","volume-title":"Solutions of Ill-Posed problems","author":"A.N. Tikhonov","year":"1977","unstructured":"Tikhonov, A.N., Arsenin, V.Y.: Solutions of Ill-Posed problems. V. H. Winston & Sons, Washington D.C. (1977)"},{"key":"6_CR22","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198522249.001.0001","volume-title":"Non-linear Time Series: A Dynamical System Approach","author":"H. Tong","year":"1990","unstructured":"Tong, H.: Non-linear Time Series: A Dynamical System Approach. Clarendon Press, Oxford (1990)"},{"key":"6_CR23","volume-title":"Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street","author":"J. Utans","year":"1991","unstructured":"Utans, J., Moody, J.E.: Selecting neural network architectures via the prediction risk: Application to corporate bond rating prediction. In: Proceedings of the First International Conference on Artificial Intelligence Applications on Wall Street. IEEE Computer Society Press, Los Alamitos (1991)"},{"key":"6_CR24","first-page":"331","volume-title":"The Mathematics of Generalization - The Proceedings of the SFI\/CNLS Workshop on Formal Approaches to Supervised Learning","author":"G. Wahba","year":"1995","unstructured":"Wahba, G., Gu, C., Wang, Y., Chappell, R.: Soft classification, a.k.a. risk estimation, via penalized log likelihood and smoothing spline analysis of variance. In: The Mathematics of Generalization - The Proceedings of the SFI\/CNLS Workshop on Formal Approaches to Supervised Learning, pp. 331\u2013359. Addison-Wesley, Reading (1995)"},{"key":"6_CR25","first-page":"1","volume":"4","author":"G. Wahba","year":"1975","unstructured":"Wahba, G., Wold, S.: A completely automatic french curve. Communications in Statistical Theory & Methods\u00a04, 1\u201317 (1975)","journal-title":"Communications in Statistical Theory & Methods"},{"key":"6_CR26","volume-title":"Proc. of the Connectionist Models Summer School","author":"A. Weigend","year":"1990","unstructured":"Weigend, A., Rumelhart, D., Hubermann, B.: Back-propagation, weight-elimination and time series prediction. In: Sejnowski, T., Hinton, G., Touretzky, D. (eds.) Proc. of the Connectionist Models Summer School. Morgan Kaufmann Publishers, San Mateo (1990)"},{"key":"6_CR27","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1162\/neco.1995.7.1.117","volume":"7","author":"P.M. Williams","year":"1995","unstructured":"Williams, P.M.: Bayesian regularization and pruning using a Laplace prior. Neural Computation\u00a07, 117\u2013143 (1995)","journal-title":"Neural Computation"}],"container-title":["Lecture Notes in Computer Science","Neural Networks: Tricks of the Trade"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-35289-8_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T10:52:15Z","timestamp":1714560735000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-35289-8_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"ISBN":["9783642352881","9783642352898"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-35289-8_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2012]]}}}