Aggregating regression procedures to improve performance

By Yuhong Yang. 2004

142 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/73439c47766634371729e56a419536ae29259dd9

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Citations in the corpus

Model selection via testing: an alternative to (penalized) maximum likelihood estimators (2006, methodology): “Further limitations of the classical methods for model selection are connected with the choice of the models which have to share some special properties: they should, for instance, be finite dimensional linear spaces generated by special bases, as in Baraud [3] or be uniformly bounded as in Yang ([6”
User-friendly introduction to PAC-Bayes bounds (2021, background): “Many aggregates share a formal similarity with the EWA of online learning and with the Gibbs posterior of the PAC-Bayes approach, we refer the reader to [144, 106, 202, 139, 203, 42, 206, 119, 116, 64, 40, 183, 65, 60, 63, 59, 62, 126, 61].”
Aggregation for Gaussian regression (2007, background): “There are relatively few results on (MS) aggregation when the estimators are allowed to be arbitrary; see [9, 13, 15, 23, 27, 40, 42, 43, 44, 45].”
Sharp Oracle Inequalities for Aggregation of Affine Estimators (2011, background): “In the statistical literature, to the best of our knowledge, theoretical foundations of aggregation procedures were first studied by Nemirovski (Nemirovski [47], Juditsky and Nemirovski [36]) and independently by a series of papers by Catoni (see [11] for an account) and Yang [61, 62, 63].”
Jackknife model averaging (2012, unknown): “There is also a rapidly-growing literature on frequentist methods for model averaging, including Buckland et al. (1997), Juditsky and Nemirovski (2000), Yang (2001, 2004), Hansen (2007), Goldenshluger (2009) and Wan et al. (2010).”
Combining Linear Regression Models (2005, background): “(For some discussion and references on the latter, see Yang 2003, 2004a and references therein.)”
Optimal rates and adaptation in the single-index model using aggregation (2007, methodology): “Cumulative versions of this algorithm can be found in Catoni (2001), Juditsky et al. (2005a), Juditsky et al. (2005b), Yang (2000b) and Yang (2004).”