Nicholas G. Polson

This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.

Bibliography

2023
On the Value of Chess Squares.
Entropy, October, 2023

Deep Learning: A Tutorial.
CoRR, 2023

2022
Chess AI: Competing Paradigms for Machine Intelligence.
Entropy, 2022

Quantum Bayes AI.
CoRR, 2022

Deep Partial Least Squares for Empirical Asset Pricing.
CoRR, 2022

2021
Merging Two Cultures: Deep and Statistical Learning.
CoRR, 2021

Karpov's Queen Sacrifices and AI.
CoRR, 2021

2020
Short Communication: Deep Fundamental Factor Models.
SIAM J. Financial Math., 2020

2019
Prediction Risk for the Horseshoe Regression.
J. Mach. Learn. Res., 2019

Scalable Data Augmentation for Deep Learning.
CoRR, 2019

Deep Fundamental Factor Models.
CoRR, 2019

2018
Bayesian Particle Tracking of Traffic Flows.
IEEE Trans. Intell. Transp. Syst., 2018

From Least Squares to Signal Processing and Particle Filtering.
Technometrics, 2018

Deep Learning: Computational Aspects.
CoRR, 2018

Deep Learning.
CoRR, 2018

Deep Learning for Predicting Asset Returns.
CoRR, 2018

Posterior Concentration for Sparse Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Deep Learning: A Bayesian Perspective.
CoRR, 2017

2016
Deep Portfolio Theory.
CoRR, 2016

Deep Learning in Finance.
CoRR, 2016

2015
Proximal Algorithms in Statistics and Machine Learning.
CoRR, 2015

2014
Augmented Markov Chain Monte Carlo Simulation for Two-Stage Stochastic Programs with Recourse.
Decis. Anal., 2014

2009
Handling Sparsity via the Horseshoe.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009


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