Machine Learning in Finance

Matthew F. Dixon (), Igor Halperin () and Paul Bilokon ()
Additional contact information
Matthew F. Dixon: Illinois Institute of Technology, Department of Applied Mathematics
Igor Halperin: New York University, Tandon School of Engineering
Paul Bilokon: Imperial College London, Department of Mathematics

in Springer Books from Springer

Date: 2020
ISBN: 978-3-030-41068-1
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Citations: View citations in EconPapers (3)

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Chapters in this book:

Ch Chapter 1 Introduction

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 10 Applications of Reinforcement Learning

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 11 Inverse Reinforcement Learning and Imitation Learning

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 12 Frontiers of Machine Learning and Finance

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 2 Probabilistic Modeling

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 3 Bayesian Regression and Gaussian Processes

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 4 Feedforward Neural Networks

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 5 Interpretability

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 6 Sequence Modeling

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 7 Probabilistic Sequence Modeling

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 8 Advanced Neural Networks

Matthew F. Dixon, Igor Halperin and Paul Bilokon

Ch Chapter 9 Introduction to Reinforcement Learning

Matthew F. Dixon, Igor Halperin and Paul Bilokon

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DOI: 10.1007/978-3-030-41068-1

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