Gradient Expectations
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Gradient Expectations
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Author : Keith L. Downing
language : en
Publisher: MIT Press
Release Date : 2023-07-18
Gradient Expectations written by Keith L. Downing and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-18 with Computers categories.
An insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI. Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world? Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems. Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today’s deep learning. Digging into the connections between predictions and gradients, and their manifestation in the brain and neural networks, is one compelling example of how Downing enriches both our understanding of such relationships and their role in strengthening AI tools. Synthesizing critical research in neuroscience, cognitive science, and connectionism, Gradient Expectations offers unique depth and breadth of perspective on predictive neural-network models, including a grasp of predictive neural circuits that enables the integration of computational models of prediction with evolutionary algorithms.
Gradient Expectations
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Author : Keith L. Downing
language : en
Publisher:
Release Date : 2023
Gradient Expectations written by Keith L. Downing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Neural networks (Computer science) categories.
An insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI. Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems. Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today's deep learning. Digging into the connections between predictions and gradients, and their manifestation in the brain and neural networks, is one compelling example of how Downing enriches both our understanding of such relationships and their role in strengthening AI tools. Synthesizing critical research in neuroscience, cognitive science, and connectionism, Gradient Expectations offers unique depth and breadth of perspective on predictive neural-network models, including a grasp of predictive neural circuits that enables the integration of computational models of prediction with evolutionary algorithms.
Inflectional Defectiveness
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Author : Andrea D. Sims
language : en
Publisher: Cambridge University Press
Release Date : 2015-11-12
Inflectional Defectiveness written by Andrea D. Sims and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-12 with Language Arts & Disciplines categories.
An accessible exploration of how defectiveness emerges from the implicative organization of paradigms and the structure of the lexicon.
Expectations And Actions
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Author : Norman T. Feather
language : en
Publisher: Routledge
Release Date : 2021-12-30
Expectations And Actions written by Norman T. Feather and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Psychology categories.
Originally published in 1982, this book examines the current status of expectancy-value models in psychology. The focus is upon cognitive models that relate action to the perceived attractiveness or aversiveness of expected consequences. A person’s behavior is seen to bear some relation to the expectations the person holds and the subjective value of the consequences that might occur following the action. Despite widespread interest in the expectancy-value (valence) approach at the time, there was no book that looked at its current status and discussed its strengths and its weaknesses, using contributions from some of the theorists who were involved in its original and subsequent development and from others who were influenced by it or had cause to examine the approach closely. This book was planned to meet this need. The chapters in this book relate to such areas as achievement motivation, attribution theory, information feedback, organizational psychology, the psychology of values and attitudes, and decision theory and in some cases they advance the expectancy-value approach further and, in other cases, point to some of its deficiencies.
Computer Aided Methods In Optimal Design And Operations
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Author : Ian David Lockhart Bogle
language : en
Publisher: World Scientific
Release Date : 2006
Computer Aided Methods In Optimal Design And Operations written by Ian David Lockhart Bogle and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
This book covers different topics on optimal design and operations with particular emphasis on chemical engineering applications. A wide range of optimization methods OCo deterministic, stochastic, global and hybrid OCo are considered. Containing papers presented at the bilateral workshop by British and Lithuanian scientists, the book brings together researchers'' contributions from different fields OCo chemical engineering including reaction and separation processes, food and biological production, as well as business cycle optimization, bankruptcy, protein analysis and bioinformatics. Sample Chapter(s). Chapter 1: Hybrid Methods for Optimisation (520 KB). Contents: Hybrid Methods for Optimisation (E S Fraga); An MILP Model for Multi-Class Data Classification (G Xu & L G Papageorgiou); Studying the Rate of Convergence of the Steepest Descent Optimisation Algorithm with Relaxation (R J Haycroft); Optimal Estimation of Parameters in Market Research Models (V Savani); A Redundancy Detection Approach to Mining Bioinformatics Data (H Camacho & A Salhi); Optimal Open-Loop Recipe Generation for Particle Size Distribution Control in Semi-Batch Emulsion Polymerisation (N Bianco & C D Immanuel); Multidimensional Scaling Using Parallel Genetic Algorithm (A Varoneckas et al.); Evaluating the Applicability of Time Temperature Integrators as Process Exploration and Validation Tools (S Bakalis et al.); Optimal Deflection Yoke Tuning (V Vaitkus et al.); and other papers. Readership: Academics, researchers, practitioners and postgraduates students in operations research and engineering."
Post School Pathways Of Migrant Origin Youth In Europe
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Author : Merike Darmody
language : en
Publisher: Taylor & Francis
Release Date : 2023-06-26
Post School Pathways Of Migrant Origin Youth In Europe written by Merike Darmody and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-26 with Education categories.
This volume explores the role of structure and agency in shaping post-school pathways for migrant-origin young people, providing new insights from countries with different migration histories and transition systems. The book collates the work of leading international scholars to cover a number of jurisdictions across Europe, looking in depth at migrant transitions in different contexts. The chapters examine the influence of different education systems, migration status, race and ethnicity, social class, gender, and resilience on the success of transitions to higher education and the labour market. The book highlights the need for host countries to put in place comprehensive policies to counter ethnic inequalities and discrimination in their education and labour market systems while facilitating and supporting immigrant youth in pursuing their post-school pathways. This timely book will be of great interest to scholars, researchers, and postgraduate students in the fields of migration studies, sociology of education, and equity in education. Policymakers will find this book useful in informing policy development in education and the labour market.
Case Studies In Applied Bayesian Data Science
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Author : Kerrie L. Mengersen
language : en
Publisher: Springer Nature
Release Date : 2020-05-28
Case Studies In Applied Bayesian Data Science written by Kerrie L. Mengersen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-28 with Mathematics categories.
Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor. The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields. While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution. The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration.
Family Cultural Capital And Student Achievement
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Author : Cheng Yong Tan
language : en
Publisher: Springer Nature
Release Date : 2020-04-09
Family Cultural Capital And Student Achievement written by Cheng Yong Tan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with Education categories.
This book focuses on the relationship between cultural capital and student achievement. It fills the gap in the literature on large-scale quantitative studies of the effects of cultural capital. In particular, the review of empirical evidence presented, especially that from studies analyzing large-scale, international data from the Programme for International Student Assessment (PISA), makes a substantial contribution to the literature. This review addresses the knowledge gap on reviews investigating the effects of different forms of cultural capital on student achievement as compared to the more established evidence base in the related field of socioeconomic status.
Optimizing Expectations
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Author : John Schulman
language : en
Publisher:
Release Date : 2016
Optimizing Expectations written by John Schulman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
This thesis is mostly focused on reinforcement learning, which is viewed as an optimization problem: maximize the expected total reward with respect to the parameters of the policy. The first part of the thesis is concerned with making policy gradient methods more sample-efficient and reliable, especially when used with expressive nonlinear function approximators such as neural networks. Chapter 3 considers how to ensure that policy updates lead to monotonic improvement, and how to optimally update a policy given a batch of sampled trajectories. After providing a theoretical analysis, we propose a practical method called trust region policy optimization (TRPO), which performs well on two challenging tasks: simulated robotic locomotion, and playing Atari games using screen images as input. Chapter 4 looks at improving sample complexity of policy gradient methods in a way that is complementary to TRPO: reducing the variance of policy gradient estimates using a state-value function. Using this method, we obtain state-of-the-art results for learning locomotion controllers for simulated 3D robots. Reinforcement learning can be viewed as a special case of optimizing an expectation, and similar optimization problems arise in other areas of machine learning; for example, in variational inference, and when using architectures that include mechanisms for memory and attention. Chapter 5 provides a unifying view of these problems, with a general calculus for obtaining gradient estimators of objectives that involve a mixture of sampled random variables and differentiable operations. This unifying view motivates applying algorithms from reinforcement learning to other prediction and probabilistic modeling problems.
Modern Trends In Controlled Stochastic Processes
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Author : Alexey Piunovskiy
language : en
Publisher: Springer Nature
Release Date : 2021-06-04
Modern Trends In Controlled Stochastic Processes written by Alexey Piunovskiy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-04 with Technology & Engineering categories.
This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference.
