Monographs on statistics and applied probability

By Trevor J. Hastie, Robert Tibshirani, Valerio Napolioni. 1990

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Citations in the corpus

Deep learning in neural networks: An overview (2014, methodology): “…in additional penalty terms (MacKay, 1992) or in methods based on validation sets (Craven & Wahba, 1979; Eubank, 1988; Golub, Heath, & Wahba, 1979; Hastie & Tibshirani, 1990; Mosteller & Tukey, 1968; Stone, 1974), Akaike’s information criterion and final prediction error (Akaike, 1970, 1973,…”
A Kernel Method for the Two-Sample-Problem (2006, methodology): “We also compared against several alternatives from the literature(where applicable): the multivariate ttest, the Friedman-Rafsky Kolmogorov-Smirnov generalisation (Smir), the Friedman-Rafsky WaldWolfowitz generalisation (Wolf), the Biau-Györfi test (Biau), and the Hall-Tajvidi test (Hall).”
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning (2020, methodology): “This metric is equivalent to regret (Berry & Fristedt, 1985), used in other ﬁelds like online learning or reinforcement learning.”
A la Carte - Learning Fast Kernels (2014, background): “Proof This follows since mixtures of Gaussians are universal approximators for densities [Silverman, 1986], as is well known in the kernel-density estimation literature.”
Probabilistic latent semantic indexing (1999, neutral): “[10] for more details on the geometry of statistical models).”
Regime Switching Vine Copula Models for Global Equity and Volatility Indices (2016, unknown): “For more details on (vine) copulas, we refer the interested reader to Joe (1997), Nelsen (2006), Kurowicka and Cooke (2006), Kurowicka and Joe (2010), Stöber and Czado (2012) or Joe (2014).”
Preoperative prediction of severe postoperative pain (2003, methodology): “Finally, we used bootstrapping techniques to validate our final model rather than split-sample or crossvalidation methods, because it has been shown in the statistical literature that the former is superior (Harrell et al., 1996; Efron and Tibshirani, 1993).”
Fuzzing: A Survey for Roadmap (2022, background): “exploitation" problem is to formulate the path transitions as a Multi-Armed Bandit (MAB) problem [14].”
Bayesian methods for neural networks (2000, methodology): “This is a standard least squares trick known as ridge regression (Marquardt and Snee, 1975; Wetherill, 1986).”
Correlation Analysis for Compositional Data (2009, background): “What is the meaning of the relation, and what is the reason for this difference?”
Self-Excited Threshold Poisson Autoregression (2013, unknown): “The series has been studied with hidden Markov models with discrete states by Zucchini and MacDonald (2009).”
Ordinal response regression models in ecology. (2000, methodology): “Through re-sampling (with replacement), the bootstrap allows one to estimate the optimism (bias) in any measure of predictive accuracy and, then, subtract the estimate of optimism from the initial apparent measure to obtain a bias-corrected estimate (Efron & Tibshirani 1993).”