Fetching the paper…
Reading the bibliography…
In a regression setup with deterministic design, we study the pure aggregation problem and introduce a natural extension from the Gaussian distribution to distributions in the exponential family.
LeCam, LucienL. (1953). On some asymptotic properties of maximum likelihood estimates and related Bayes’ estimates. Univ. California Publ. Statist. 1 277–329
1953
Earlier work this paper cites.
Akaike, H.H. (1973). Information theory and an extension of the maximum likelihood principle. In Second International Symposium on Information Theory (Tsahkadsor, 1971) 267–281. Akad. Kiadó, Budapest
1971
Earlier work this paper cites.
Barndorff-Nielsen, OleO. (1978). Information and Exponential Families in Statistical Theory. Wiley, Chichester
1978
Earlier work this paper cites.
White, HalbertH. (1982). Maximum likelihood estimation of misspecified models. Econometrica 50 1–25
1982
Earlier work this paper cites.
Fahrmeir, LudwigL. andKaufmann, HeinzH. (1985). Consistency and asymptotic normality of the maximum likelihood estimator in generalized linear models. Ann. Statist. 13 342–368
1985
Earlier work this paper cites.
Brown, Lawrence D.L. D. (1986). Fundamentals of Statistical Exponential Families with Applications in Statistical Decision Theory. Institute of Mathematical Statistics Lecture Notes—Monograph Series 9. IMS, Hayward, CA
1986
Earlier work this paper cites.
McCullagh, P.P. andNelder, J. A.J. A. (1989). Generalized Linear Models, 2nd ed. Chapman and Hall, London
1989
Earlier work this paper cites.
Freund, Y.Y. andSchapire, R. E.R. E. (1996). Experiments with a new boosting algorithm. In International Conference on Machine Learning
1996
Earlier work this paper cites.
Lehmann, E. L.E. L. andCasella, GeorgeG. (1998). Theory of Point Estimation, 2nd ed. Springer, New York
1998
Earlier work this paper cites.
Nemirovski, ArkadiA. (2000). Topics in non-parametric statistics. In Lectures on Probability Theory and Statistics (Saint-Flour, 1998). Lecture Notes in Math. 1738 85–277. Springer, Berlin
1998
Earlier work this paper cites.
Breiman, L.L. (1999). Prediction games and arcing algorithms. Neural Comput. 11 1493–1517
1999
Earlier work this paper cites.
Ekeland, IvarI. andTémam, RogerR. (1999). Convex Analysis and Variational Problems. Classics in Applied Mathematics 28. SIAM, Philadelphia, PA
1999
Earlier work this paper cites.
Friedman, JeromeJ., Hastie, TrevorT. andTibshirani, RobertR. (2000). Additive logistic regression: A statistical view of boosting (with discussion). Ann. Statist. 28 337–407
2000
Earlier work this paper cites.
Juditsky, AnatoliA. andNemirovski, ArkadiiA. (2000). Functional aggregation for nonparametric regression. Ann. Statist. 28 681–712
2000
Earlier work this paper cites.
Yang, YuhongY. (2000). Mixing strategies for density estimation. Ann. Statist. 28 75–87
2000
Earlier work this paper cites.
Catoni, OlivierO. (2004). Statistical Learning Theory and Stochastic Optimization. Lecture Notes in Math. 1851. Springer, Berlin. Lecture notes from the 31st Summer School on Probability Theory held in Saint-Flour, July 8–25, 2001
2001
Cited alongside, same era.
Tsybakov, A. B.A. B. (2003). Optimal rates of aggregation. In COLT (B.B. Schölkopf andM. K.M. K. Warmuth, eds.). Lecture Notes in Computer Science 2777 303–313. Springer, Berlin
2003
Cited alongside, same era.
Greenshtein, EitanE. andRitov, Ya’acovY. (2004). Persistence in high-dimensional linear predictor selection and the virtue of overparametrization. Bernoulli 10 971–988
2004
Cited alongside, same era.
Yang, YuhongY. (2004). Aggregating regression procedures to improve performance. Bernoulli 10 25–47
2004
Cited alongside, same era.
Boucheron, StéphaneS., Bousquet, OlivierO. andLugosi, GáborG. (2005). Theory of classification: A survey of some recent advances. ESAIM Probab. Stat. 9 323–375
Juditsky, A.A., Rigollet, P.P. andTsybakov, A. B.A. B. (2008). Learning by mirror averaging. Ann. Statist. 36 2183–2206
2008
Later among the works it cites.
Mease, D.D. andWyner, A.A. (2008). Evidence contrary to the statistical view of boosting. J. Mach. Learn. Res. 9 131–156
2008
Later among the works it cites.
Nemirovski, A.A., Juditsky, A.A., Lan, G.G. andShapiro, A.A. (2008). Robust stochastic approximation approach to stochastic programming. SIAM J. Optim. 19 1574–1609
2008
Later among the works it cites.
Lecué, GuillaumeG. andMendelson, ShaharS. (2009). Aggregation via empirical risk minimization. Probab. Theory Related Fields 145 591–613
2009
Closest in time.
Mitchell, CharlesC. andvan de Geer, SaraS. (2009). General oracle inequalities for model selection. Electron. J. Stat. 3 176–204
2009
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2005
Cited alongside, same era.
Greenshtein, EitanE. (2006). Best subset selection, persistence in high-dimensional statistical learning and optimization under l 1 l_{1} constraint. Ann. Statist. 34 2367–2386
2006
Cited alongside, same era.
Belomestny, DenisD. andSpokoiny, VladimirV. (2007). Spatial aggregation of local likelihood estimates with applications to classification. Ann. Statist. 35 2287–2311
2007
Cited alongside, same era.
Bunea, FlorentinaF., Tsybakov, Alexandre B.A. B. andWegkamp, Marten H.M. H. (2007). Aggregation for Gaussian regression. Ann. Statist. 35 1674–1697
2007
Cited alongside, same era.
Dalalyan, Arnak S.A. S. andTsybakov, Alexandre B.A. B. (2007). Aggregation by exponential weighting and sharp oracle inequalities. In Learning Theory. Lecture Notes in Computer Science 4539 97–111. Springer, Berlin
2007
Cited alongside, same era.
Lecué, GuillaumeG. (2007). Simultaneous adaptation to the margin and to complexity in classification. Ann. Statist. 35 1698–1721
2007
Cited alongside, same era.
Lounici, K.K. (2007). Generalized mirror averaging and D D -convex aggregation. Math. Methods Statist. 16 246–259
2007
Cited alongside, same era.
Massart, PascalP. (2007). Concentration Inequalities and Model Selection. Lecture Notes in Math. 1896. Springer, Berlin
2007
Cited alongside, same era.
Alquier, PierreP. andLounici, KarimK. (2011). PAC-Bayesian bounds for sparse regression estimation with exponential weights. Electron. J. Stat. 5 127–145
2011
Closest in time.
Dalalyan, A.A. andSalmon, J.J. (2011). Sharp oracle inequalities for aggregation of affine estimators. Available at arXiv: \arxivurl
2011
Closest in time.
Raskutti, G.G., Wainwright, M. J.M. J. andYu, B.B. (2011). Minimax rates of estimation for high-dimensional linear regression over ℓ q \ell_{q} -balls. IEEE Trans. Inform. Theory 57 6976–6994
2011
Closest in time.
Rigollet, PhilippeP. andTsybakov, AlexandreA. (2011). Exponential screening and optimal rates of sparse estimation. Ann. Statist. 39 731–771
2011
Closest in time.
Bartlett, P. L.P. L., Mendelson, S.S. andNeeman, J.J. (2012). ℓ 1 \ell_{1} -regularized linear regression: Persistence and oracle inequalities. Probab. Theory Related Fields
2012
Closest in time.
Lecué, G.G. (2012). Empirical risk minimization is optimal for the convex aggregation problem. Bernoulli
2012
Closest in time.
Rigollet, P.P. (2012). Supplement to “Kullback–Leibler aggregation and misspecified generalized linear models.” DOI: \doiurl
2012
Closest in time.
Rigollet, PhilippeP. andTsybakov, AlexandreA. (2012). Sparse estimation by exponential weighting. Statist. Sci
2012
Closest in time.
Koltchinskii, VladimirV. (2011). Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems. Lecture Notes in Math. 2033. Springer, Heidelberg
2033
Closest in time.