rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: QUANTUM MACHINE LEARNING AND OPTIMISATION IN FINANCE
    sub title: on the road to quantum advantage
  name:
    name part: Jacquier, Antoine.
    role:
      role term: creator
  name:
    name part: Kondratyev, Oleksiy.
  name:
    name part: Lipton, Alexander.
  name:
    name part: López de Prado, Marcos Mailoc.
  type of resource: text
  origin info:
    place:
      place term: xx
    place:
      place term: S.l.]
    publisher: PACKT PUBLISHING LIMITED
    date issued: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: Learn the principles of quantum machine learning and how to apply them in finance. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key Features Discover how to solve optimisation problems on quantum computers that can provide a speedup edge over classical methods Use methods of analogue and digital quantum computing to build powerful generative models Create the latest algorithms that work on Noisy Intermediate-Scale Quantum (NISQ) computers Book Description With recent advances in quantum computing technology, we finally reached the era of Noisy Intermediate-Scale Quantum (NISQ) computing. NISQ-era quantum computers are powerful enough to test quantum computing algorithms and solve hard real-world problems faster than classical hardware. Speedup is so important in financial applications, ranging from analysing huge amounts of customer data to high frequency trading. This is where quantum computing can give you the edge. Quantum Machine Learning and Optimisation in Finance shows you how to create hybrid quantum-classical machine learning and optimisation models that can harness the power of NISQ hardware. This book will take you through the real-world productive applications of quantum computing. The book explores the main quantum computing algorithms implementable on existing NISQ devices and highlights a range of financial applications that can benefit from this new quantum computing paradigm. This book will help you be one of the first in the finance industry to use quantum machine learning models to solve classically hard real-world problems. We may have moved past the point of quantum computing supremacy, but our quest for establishing quantum computing advantage has just begun! What you will learn Train parameterised quantum circuits as generative models that excel on NISQ hardware Solve hard optimisation problems Apply quantum boosting to financial applications Learn how the variational quantum eigensolver and the quantum approxi…
  table of contents: Cover -- Copyright -- Contributors -- Table of Contents -- Preface -- Chapter 1: The Principles of Quantum Mechanics -- Part I -- Chapter 2: Adiabatic Quantum Computing -- Chapter 3: Quadratic Unconstrained Binary Optimisation -- Chapter 4: Quantum Boosting -- Chapter 5: Quantum Boltzmann Machine -- Part II -- Chapter 6: Qubits and Quantum Logic Gates -- Chapter 7: Parameterised Quantum Circuits and Data Encoding -- Chapter 8: Quantum Neural Network -- Chapter 9: Quantum Neural Network -- Chapter 10: Variational Quantum Eigensolver
  table of contents: Chapter 11: Quantum Approximate Optimisation Algorithm -- Chapter 12: The Power of Parameterised Quantum Circuits -- Chapter 13: Looking Ahead -- Index -- Other Books You Might Enjoy -- Packt Page
  note: Antoine Jacquier, Oleksiy Kondratyev ; foreword by Alexander Lipton & Marcos López de Prado.
  subject:
    topic: Finance
    topic: Data processing
  subject:
    topic: Finance
    topic: Mathematical models
  subject:
    topic: Machine learning
  subject:
    topic: Quantum computing
  subject:
    topic: Finance
    topic: Data processing
  subject:
    topic: Finance
    topic: Mathematical models
  subject:
    topic: Machine learning
  subject:
    topic: Quantum computing
  classification: HG104
  classification: 332.028541
  related item:
    identifier: (OCoLC)1335115209
  related item:
    title info:
      title: Expert insight
  identifier: 9781801817875
  identifier: 1801817871
  identifier: 1801813574
  identifier: 9781801813570
  identifier: 9781801813570 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 221102
    record change date: 20260130164258.8
    record identifier: in00004672831
    language of cataloging:
      language term: eng