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Term Structure and Real-Time Learning

Term Structure and Real-Time Learning
Author: Pablo Aguilar
Publisher:
Total Pages: 55
Release: 2018
Genre:
ISBN:

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This paper introduces the term structure of interest rates into a medium-scale DSGE model. This extension results in a multi-period forecasting model that is estimated under both adaptive learning and rational expectations. Term structure information enables us to characterize agents' expectations in real time, which addresses an imperfect information issue mostly neglected in the adaptive learning literature. Relative to the rational expectations version, our estimated DSGE model under adaptive learning largely improves the model fit to the data, which include not just macroeconomic data but also the yield curve and the consumption growth and inflation forecasts reported in the Survey of Professional Forecasters. Moreover, the estimation results show that most endogenous sources of aggregate persistence are dramatically undercut when adaptive learning based on multi-period forecasting is incorporated through the term structure of interest rates.


Learning in Real Time

Learning in Real Time
Author: Andrew John Patton
Publisher:
Total Pages: 56
Release: 2007
Genre: Economic forecasting
ISBN:

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Handbook of Neural Network Signal Processing

Handbook of Neural Network Signal Processing
Author: Yu Hen Hu
Publisher: CRC Press
Total Pages: 386
Release: 2018-10-03
Genre: Technology & Engineering
ISBN: 1351836307

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The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.


Real-time Systems Education

Real-time Systems Education
Author:
Publisher:
Total Pages: 144
Release: 1997
Genre: Real-time data processing
ISBN:

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Monitoring Privately-held Firms' Default Risk in Real Time: A Signal-Knowledge Transfer Learning Model

Monitoring Privately-held Firms' Default Risk in Real Time: A Signal-Knowledge Transfer Learning Model
Author: Mr. Jorge A Chan-Lau
Publisher: International Monetary Fund
Total Pages: 45
Release: 2024-06-07
Genre: Business & Economics
ISBN:

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We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to construct a probability of default (PD) function. This function integrates high-frequency, market-based, aggregate distress signals with low-frequency, firm-level financial ratios, and macroeconomic indicators. When provided with private firms' financial ratios, the model, which we name signal-knowledge transfer learning model (SKTL), transfers insights gained from 35 thousand publicly-traded firms to more than 4 million private-held ones and performs well as an ordinal measure of privately-held firms' default risk.


Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence

Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence
Author: Gogate, Lakshmi
Publisher: IGI Global
Total Pages: 451
Release: 2013-02-28
Genre: Computers
ISBN: 1466629746

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The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.


The Handbook of Blended Learning

The Handbook of Blended Learning
Author: Curtis J. Bonk
Publisher: Wiley + ORM
Total Pages: 502
Release: 2012-06-29
Genre: Business & Economics
ISBN: 1118429575

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This comprehensive resource highlights the most recent practices and trends in blended learning from a global perspective and provides targeted information for specific blended learning situations. You'll find examples of learning options that combine face-to-face instruction with online learning in the workplace, more formal academic settings, and the military. Across these environments, the book focuses on real-world practices and includes contributors from a broad range of fields including trainers, consultants, professors, university presidents, distance-learning center directors, learning strategists and evangelists, general managers of learning, CEOs, chancellors, deans, and directors of global talent and organizational development. This diversity and breadth will help you understand the wide range of possibilities available when designing blended learning environments. Order your copy today!


Algorithms and Architectures for Real-Time Control 1991

Algorithms and Architectures for Real-Time Control 1991
Author: P.J. Fleming
Publisher: Elsevier
Total Pages: 279
Release: 2014-07-22
Genre: Technology & Engineering
ISBN: 1483298256

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Computer scientists have long appreciated that the relationship between algorithms and architecture is crucial. Broadly speaking the more specialized the architecture is to a particular algorithm then the more efficient will be the computation. The penalty is that the architecture will become useless for computing anything other than that algorithm. This message holds for the algorithms used in real-time automatic control as much as any other field. These Proceedings will provide researchers in this field with a useful up-to-date reference source of recent developments.


Fast Cycle Time

Fast Cycle Time
Author: Christopher Meyer
Publisher: Simon and Schuster
Total Pages: 312
Release: 2010-05-11
Genre: Business & Economics
ISBN: 1439137676

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Today, tens of thousands of companies are struggling to become "time-based" competitors, inspired by such corporations as Motorola, General Electric, Citicorp, and a myriad of others who have cut production time in half—or more. But until now, the literature has focused on the theory and philosophy of fast cycle time, rather than the tools and techniques for implementing it. Here, for the first time, Christopher Meyer, an internationally recognized expert in cycle time reduction, presents a step-by-step blueprint for transforming traditional companies into fast cycle competitors. Meyer argues that fast cycle time is achieved not by working faster, but by aligning the organization's purpose, strategy and structure. He demonstrates how the product development cycle must become a learning laboratory in which the four continuous elements "Design, Fabricate, Assemble, and Test" are analyzed with the intent to improve strategy in the next business cycle. Analyzing strategy and core processes enables management to detect and correct problems earlier, and leverage knowledge for improved innovation and increased value for customers. Employing an ongoing case study, Core Products, Inc., throughout the text, Meyer shows how to redesign the organization for manufacturability and assembly, how to implement multifunctional teams that work, how to analyze and map critical cycle time interdependencies such as "co-location," and how to measure the impact of cycle time on business performance. Meyer's practical approach provides a simple methodology for organizations to deliver products to customers rapidly, accurately, and reliably. "Chris Meyer interrelates many pieces that we have all read about in different places into a coherent guide to making it happen. Ironically, as Meyer shows, implementing fast cycle time means almost the opposite of what most American managers are inclined to do...Many years of practical experience have shown Meyer and his colleagues the wisdom of a paradox—that to speed up you often have to slow down." —From the Foreword by Peter M. Senge


Deep and Shallow

Deep and Shallow
Author: Shlomo Dubnov
Publisher: CRC Press
Total Pages: 430
Release: 2023-12-08
Genre: Computers
ISBN: 1000984532

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Providing an essential and unique bridge between the theories of signal processing, machine learning, and artificial intelligence (AI) in music, this book provides a holistic overview of foundational ideas in music, from the physical and mathematical properties of sound to symbolic representations. Combining signals and language models in one place, this book explores how sound may be represented and manipulated by computer systems, and how our devices may come to recognize particular sonic patterns as musically meaningful or creative through the lens of information theory. Introducing popular fundamental ideas in AI at a comfortable pace, more complex discussions around implementations and implications in musical creativity are gradually incorporated as the book progresses. Each chapter is accompanied by guided programming activities designed to familiarize readers with practical implications of discussed theory, without the frustrations of free-form coding. Surveying state-of-the art methods in applications of deep neural networks to audio and sound computing, as well as offering a research perspective that suggests future challenges in music and AI research, this book appeals to both students of AI and music, as well as industry professionals in the fields of machine learning, music, and AI.