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2
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33746043351
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A randomized online learning algorithm for better variance control
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COLT 2006. Proceedings of the 19th Annual Conference on Learning Theory, Springer, Heidelberg
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Audibert, J.-Y.: A randomized online learning algorithm for better variance control. In: COLT 2006. Proceedings of the 19th Annual Conference on Learning Theory. LNCS (LNAI), vol. 4005, pp. 392-407. Springer, Heidelberg (2006)
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Audibert, J.-Y.1
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1-penalized least squares. In: Lugosi, G., Simon, H.U. (eds.) COLT 2006. LNCS (LNAI), 4005, pp. 379-391. Springer, Heidelberg (2006)
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5
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38049043619
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Aggregation for gaussian regression
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to appear
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Bunea, F., Tsybakov, A.B., Wegkamp, M.H.: Aggregation for gaussian regression. Annals of Statistics, to appear (2007), http://www.stat.fsu.edu/ ~wegkamp
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Annals of Statistics
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Bunea, F.1
Tsybakov, A.B.2
Wegkamp, M.H.3
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6
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38049017702
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Sparsity oracle inequalities for the Lasso
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Submitted
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Bunea, F., Tsybakov, A.B., Wegkamp, M.H.: Sparsity oracle inequalities for the Lasso, Submitted (2006)
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Bunea, F.1
Tsybakov, A.B.2
Wegkamp, M.H.3
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7
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34548275795
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The Dantzig selector: Statistical estimation when p is much larger than n
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to appear
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Candes, E., Tao, T.: The Dantzig selector: statistical estimation when p is much larger than n. Annals of Statistics, to appear (2007)
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Annals of Statistics
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Candes, E.1
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8
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38049048402
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Universal, aggregation rules with exact bias bounds. Preprint n.510, Laboratoire de Probabilités et Modèles Aléatoires, Universités Paris 6 and Paris 7
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Catoni, O.: Universal, aggregation rules with exact bias bounds. Preprint n.510, Laboratoire de Probabilités et Modèles Aléatoires, Universités Paris 6 and Paris 7 (1999), http://www.proba.jussieu.fr/ mathdoc/preprints/index.html#1999
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Catoni, O.1
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9
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0345234052
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Statistical Learning Theory and Stochastic Optimization
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Ecole d'été de Probabilités de Saint-Flour 2001, Springer, Heidelberg
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Catoni, O.: Statistical Learning Theory and Stochastic Optimization. In: Ecole d'été de Probabilités de Saint-Flour 2001. Lecture Notes in Mathematics, Springer, Heidelberg (2004)
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10
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4544304381
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On the generalization ability of on-line learning algorithms
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Cesa-Bianchi, N., Conconi, A., Gentile, G.: On the generalization ability of on-line learning algorithms. IEEE Trans. on Information Theory 50, 2050-2057 (2004)
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Cesa-Bianchi, N.1
Conconi, A.2
Gentile, G.3
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11
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84926078662
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Cambridge University Press, New York
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Cesa-Bianchi, N., Lugosi, G.: Prediction, Learning, and Games. Cambridge University Press, New York (2006)
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Prediction, Learning, and Games
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Cesa-Bianchi, N.1
Lugosi, G.2
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33144483155
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Stable Recovery of Sparse Overcomplete Representations in the Presence of Noise
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Donoho, D.L., Elad, M., Temlyakov, V.: Stable Recovery of Sparse Overcomplete Representations in the Presence of Noise. IEEE Trans. on Information Theory 52, 6-18 (2006)
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Donoho, D.L.1
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Learning by mirror averaging
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Juditsky, A., Rigollet, P., Tsybakov, A.: Learning by mirror averaging. Preprint n, Laboratoire de Probabilités et Modèle aléatoires, Universités Paris 6 and Paris 7, (2005). n. 1034, https://hal.ccsd.cnrs.fr/ccsd-00014097
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Recursive aggregation of estimators via the Mirror Descent Algorithm with averaging
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Juditsky, A.B., Nazin, A.V., Tsybakov, A.B., Vayatis, N.: Recursive aggregation of estimators via the Mirror Descent Algorithm with averaging. Problems of Information Transmission 41, 368-384 (2005)
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Problems of Information Transmission
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, pp. 368-384
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Juditsky, A.B.1
Nazin, A.V.2
Tsybakov, A.B.3
Vayatis, N.4
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15
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38049085467
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Sparsity in penalized empirical risk minimization
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Koltchinskii, V.: Sparsity in penalized empirical risk minimization, Submitted (2006)
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Information theory and mixing least-square regressions
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Leung, G.1
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The Skorokhod embedding problem and its offspring
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Tsybakov, A.B.: Optimal rates of aggregation. In: Schölkopf, B., Warmuth, M. (eds.) Computational Learning Theory and Kernel Machines. LNCS (LNAI), vol. 2777, pp. 303-313. Springer, Heidelberg (2003)
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High dimensional generalized linear models and the Lasso
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No. 133. Seminar für Statistik, ETH, Zürich
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Aggregating Strategies
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From epsilon-entropy to KL-complexity: Analysis of minimum information complexity density estimation
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Zhang, T.: From epsilon-entropy to KL-complexity: analysis of minimum information complexity density estimation. Annals of Statistics, to appear (2007)
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