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Bayesian Hypothesis Testing: Redux
Hedibert F. Lopes, Nicholas G. Polson
Bayesian hypothesis testing is re-examined from the perspective of an a priori assessment of the test statistic distribution under the alternative. By assessing the distribution of…
Deep Learning
Nicholas G. Polson, Vadim O. Sokolov
Deep learning (DL) is a high dimensional data reduction technique for constructing high-dimensional predictors in input-output models. DL is a form of machine learning that uses hi…
Deep Learning: Computational Aspects
Nicholas Polson, Vadim Sokolov
In this article we review computational aspects of Deep Learning (DL). Deep learning uses network architectures consisting of hierarchical layers of latent variables to construct p…
Riemann Hypothesis: a GGC factorisation
Nicholas G. Polson
A GGC (Generalized Gamma Convolution) representation of Riemann's Xi-function is constructed.
Deep Learning for Predicting Asset Returns
Guanhao Feng, Jingyu He, Nicholas G. Polson
Deep learning searches for nonlinear factors for predicting asset returns. Predictability is achieved via multiple layers of composite factors as opposed to additive ones. Viewed i…
Riemann, Thorin, van Dantzig Pairs, Wald Couples and Hadamard Factorisation
Nicholas G. Polson
The Hadamard-Weierstrass factorisation of an entire function in the Laguerre-Pólya class is dual to a pair of probabilistic objects: a van Dantzig pair of characteristic functions…