Advanced techniques optimization machine (17 Ergebnisse)

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hardcover. Zustand: Very Good.

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Zustand: New. pp. 550.

Sprache: Englisch
Verlag: Elsevier Science Publishing Co Inc, United States, San Diego, 2020
- Softcover
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Paperback. Zustand: Very Good. Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Trading and Portfolio Management. This edition includes new chapters on algorithmic trading, advanced trading analytics, regr…ession analysis, optimization, and advanced statistical methods. Increasing its focus on trading strategies and models, this edition includes new insights into the ever-changing financial environment, pre-trade and post-trade analysis, liquidation cost & risk analysis, and compliance and regulatory reporting requirements. Highlighting new investment techniques, this book includes material to assist in the best execution process, model validation, quality and assurance testing, limit order modeling, and smart order routing analysis. Includes advanced modeling techniques using machine learning, predictive analytics, and neural networks. The text provides readers with a suite of transaction cost analysis functions packaged as a TCA library. These programming tools are accessible via numerous software applications and programming languages. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

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Advanced Techniques for Optimal Sizing of Analog Integrated Circuits: Quantum Computing, Machine Learning, and Bio-inspired Optimization
Hoang, Trang; Do, Thinh Quang; Nguyen, Thang Quoc; Nguyen, Hoang Trong; Zhang, Lihong; Dobre, Octavia A.; Duong, Trung Q.
- Hardcover
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Zustand: New. In English.

Advanced Techniques for Optimal Sizing of Analog Integrated Circuits: Quantum Computing, Machine Learning, and Bio-inspired Optimization
Hoang, Trang; Do, Thinh Quang; Nguyen, Thang Quoc; Nguyen, Hoang Trong; Zhang, Lihong; Dobre, Octavia A.; Duong, Trung Q.
- Hardcover
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Advanced Techniques for Optimal Sizing of Analog Integrated Circuits: Quantum Computing, Machine Learning and Bio-inspired Optimization
Hoang, Trang/ Do, Thinh Quang/ Nguyen, Thang Quoc/ Nguyen, Hoang Trong/ Zhang, Lihong
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Hardcover. Zustand: Brand New. In Stock.

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Zustand: New. Provides insight into all necessary components of algorithmic trading including: transaction cost analysis, market impact estimation, risk modeling and optimization, and advanced examination of trading algorithms and corresponding data requirements.

Advanced Techniques for Optimal Sizing of Analog I ntegrated Circuits Quantum Computing, Machine L earning, and Bioinspired Optimization
Hoang, Trang/ Do, Thinh Quang/ Nguyen, Thang Quoc/ Nguyen, Hoang Trong/ Zhang, Lihong
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Hardcover. Zustand: Brand New. 368 pages. 6.00x0.44x9.00 inches. In Stock.

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Zustand: Gut. Zustand: Gut | Seiten: 614 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Zustand: New. 2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

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Buch. Zustand: Neu. Neuware - A novel and authoritative approach to quantum machine learning in integrated circuits design optimization In Advanced Techniques for Optimal Sizing of Analog Integrated Circuits, a team of distinguished researchers deliver a comprehensive discussion of the theory, models, methodologies, practical im…plementation, and utilization of integrated circuit (IC) design. The authors explain IC design optimization, demonstrating cost-effective and time-saving design approaches, as well as techniques likely to be impactful in the near future. The book covers major topics in the field, describing key concepts, recent advances, effective algorithms, and pressing challenges associated with analog circuit sizing optimization. It discusses using both animal and human-inspired optimization algorithms to create basic and quantum machine learning methods. Readers will also find: - A novel approach to quantum machine learning in integrated circuit design optimization- A range of introductory and advanced topics suitable for students, advanced professionals, and researchers- Detailed illustrations that clarify abstract, complicated engineering concepts- Complete treatments of animal behavior-inspired optimization algorithms, including particle swarm optimization, firefly algorithm, cuckoo search, and bat algorithm Perfect for researchers in engineering, computer scientists, professors, and senior undergraduate and graduate students in integrated circuit design, this book will also benefit students of machine learning, computer science, quantum computing, and optimization.

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Taschenbuch. Zustand: Neu. Neuware - Algorithmic Trading Methods: Applications using Advanced Statistics, Optimization, and Machine Learning Techniques, Second Edition, is a sequel to The Science of Algorithmic Trading and Portfolio Management. This edition includes new chapters on algorithmic trading, advanced trading analytics…, regression analysis, optimization, and advanced statistical methods. Increasing its focus on trading strategies and models, this edition includes new insights into the ever-changing financial environment, pre-trade and post-trade analysis, liquidation cost & risk analysis, and compliance and regulatory reporting requirements. Highlighting new investment techniques, this book includes material to assist in the best execution process, model validation, quality and assurance testing, limit order modeling, and smart order routing analysis. Includes advanced modeling techniques using machine learning, predictive analytics, and neural networks. The text provides readers with a suite of transaction cost analysis functions packaged as a TCA library. These programming tools are accessible via numerous software applications and programming languages.

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Taschenbuch. Zustand: Neu. Advanced Techniques in Optimization for Machine Learning and Imaging | Alessandro Benfenati (u. a.) | Taschenbuch | Springer INdAM Series | x | Englisch | 2025 | Springer | EAN 9789819767717 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hart…mann[at]springer[dot]com | Anbieter: preigu.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either re…visiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop 'Advanced Techniques in Optimization for Machine learning and Imaging' held in Roma, Italy, on June 20-24, 2022.The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisitin…g consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop 'Advanced Techniques in Optimization for Machine learning and Imaging' held in Roma, Italy, on June 20-24, 2022.The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms.