Matthew Dixon

According to our database1, Matthew Dixon authored at least 16 papers between 2003 and 2021.

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Bibliography

2021
Information-Corrected Estimation: A Generalization Error Reducing Parameter Estimation Method.
Entropy, 2021

MS-nowcasting: Operational Precipitation Nowcasting with Convolutional LSTMs at Microsoft Weather.
CoRR, 2021

2020
Financial Forecasting With α-RNNs: A Time Series Modeling Approach.
Frontiers Appl. Math. Stat., 2020

G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning.
CoRR, 2020

2018
Sequence classification of the limit order book using recurrent neural networks.
J. Comput. Sci., 2018

2017
Classification-based financial markets prediction using deep neural networks.
Algorithmic Finance, 2017

2016
Classiffication-based Financial Markets Prediction using Deep Neural Networks.
CoRR, 2016

Workshop on high-performance computational finance.
Concurr. Comput. Pract. Exp., 2016

A portable, extensible and fast stochastic volatility model calibration using multi and many-core processors.
Concurr. Comput. Pract. Exp., 2016

2015
Implementing deep neural networks for financial market prediction on the Intel Xeon Phi.
Proceedings of the 8th Workshop on High Performance Computational Finance, 2015

2014
A Bayesian approach to ranking private companies based on predictive indicators.
AI Commun., 2014

Accelerating option risk analytics in <i>R</i> using GPUs.
Proceedings of the 2014 Spring Simulation Multiconference, 2014

A portable and fast stochastic volatility model calibration using multi and many-core processors.
Proceedings of the 7th Workshop on High Performance Computational Finance, 2014

2013
Calibration of stochastic volatility models on a multi-core CPU cluster.
Proceedings of WHPCF'13: 6th Workshop on High Performance Computational Finance, 2013

2009
Acceleration of market value-at-risk estimation.
Proceedings of the 2nd Workshop on High Performance Computational Finance, 2009

2003
Information Technology Practitioner Skills in Europe: Current Status and Challenges for the Future.
Proceedings of the Computer Science in Perspective, Essays Dedicated to Thomas Ottmann, 2003


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