Items related to Learning Theory from First Principles (Adaptive Computation...
Learning Theory from First Principles (Adaptive Computation and Machine Learning series) - Hardcover
Synopsis
A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory.
Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. . In this accessible textbook, Francis Bach presents the foundations and latest advances of learning theory for graduate students as well as researchers who want to acquire a basic mathematical understanding of the most widely used machine learning architectures. Taking the position that learning theory does not exist outside of algorithms that can be run in practice, this book focuses on the theoretical analysis of learning algorithms as it relates to their practical performance. Bach provides the simplest formulations that can be derived from first principles, constructing mathematically rigorous results and proofs without overwhelming students.
- Provides a balanced and unified treatment of most prevalent machine learning methods
- Emphasizes practical application and features only commonly used algorithmic frameworks
- Covers modern topics not found in existing texts, such as overparameterized models and structured prediction
- Integrates coverage of statistical theory, optimization theory, and approximation theory
- Focuses on adaptivity, allowing distinctions between various learning techniques
- Hands-on experiments, illustrative examples, and accompanying code link theoretical guarantees to practical behaviors
"synopsis" may belong to another edition of this title.
About the Author
Francis Bach is a researcher at Inria where he leads the machine learning team which is part of the Computer Science department at Ecole Normale Supérieure. His research focuses on machine learning and optimization.
"About this title" may belong to another edition of this title.
Search results for Learning Theory from First Principles (Adaptive Computation...
Stock Image
Learning Theory from First Principles
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Hardback. Condition: Good. A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory. Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. . In this accessible textbook, Francis Bach presents the foundations and latest advances of learning theory for graduate students as well as researchers who want to acquire a basic mathematical understanding of the most widely used machine learning architectures. Taking the position that learning theory does not exist outside of algorithms that can be run in practice, this book focuses on the theoretical analysis of learning algorithms as it relates to their practical performance. Bach provides the simplest formulations that can be derived from first principles, constructing mathematically rigorous results and proofs without overwhelming students. Provides a balanced and unified treatment of most prevalent machine learning methods Emphasizes practical application and features only commonly used algorithmic frameworks Covers modern topics not found in existing texts, such as overparameterized models and structured prediction Integrates coverage of statistical theory, optimization theory, and approximation theory Focuses on adaptivity, allowing distinctions between various learning techniques Hands-on experiments, illustrative examples, and accompanying code link theoretical guarantees to practical behaviors. Seller Inventory # 00108864784
Stock Image
Learning Theory from First Principles (Adaptive Computation and Machine Learning series)
Seller: Bellwetherbooks, McKeesport, PA, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Good. Bruise/tear to cover. Seller Inventory # mon0000053810
Stock Image
Learning Theory from First Principles
Seller: World of Books Inc, Montgomery, IL, U.S.A.
Seller rating 4 out of 5 stars
Hardback. Condition: Good. A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory. Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. . In this accessible textbook, Francis Bach presents the foundations and latest advances of learning theory for graduate students as well as researchers who want to acquire a basic mathematical understanding of the most widely used machine learning architectures. Taking the position that learning theory does not exist outside of algorithms that can be run in practice, this book focuses on the theoretical analysis of learning algorithms as it relates to their practical performance. Bach provides the simplest formulations that can be derived from first principles, constructing mathematically rigorous results and proofs without overwhelming students. Provides a balanced and unified treatment of most prevalent machine learning methods Emphasizes practical application and features only commonly used algorithmic frameworks Covers modern topics not found in existing texts, such as overparameterized models and structured prediction Integrates coverage of statistical theory, optimization theory, and approximation theory Focuses on adaptivity, allowing distinctions between various learning techniques Hands-on experiments, illustrative examples, and accompanying code link theoretical guarantees to practical behaviors. Seller Inventory # CIN0262049449G
Stock Image
Learning Theory from First Principles (Adaptive Computation and Machine Learning series)
Seller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: Very Good. Seller Inventory # mon0004251961
Seller Image
Learning Theory from First Principles (Adaptive Computation and Machine Learning)
Seller: WeBuyBooks, Rossendale, LANCS, United Kingdom
Seller rating 5 out of 5 stars
hardcover. Condition: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind. Seller Inventory # rev1621120375
Buy Used
US$ 53.49
US$ 13.88 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Stock Image
Learning Theory from First Principles (Adaptive Computation and Machine Learning series)
Seller: CampusBear, Coppell, TX, U.S.A.
Seller rating 4 out of 5 stars
hardcover. Condition: As New. Complete and unmarked. All pages present and readable, binding tight. No highlighting, underlining, or writing anywhere in the text. Cover and spine show minimal to no shelf wear. May have a remainder mark, a price sticker or its residue, or a previous owner's name on the inside cover. Access codes, CDs, DVDs, and other bundled supplements may not be included and should be assumed used or missing unless the listing explicitly states otherwise. Seller Inventory # B1362C00773U
Stock Image
Learning Theory from First Principles
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 47516601-n
Stock Image
Learning Theory from First Principles (Adaptive Computation and Machine Learning series)
Seller: INDOO, Avenel, NJ, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 9780262049443
Stock Image
Learning Theory from First Principles (Hardcover)
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory.A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory.Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. . In this accessible textbook, Francis Bach presents the foundations and latest advances of learning theory for graduate students as well as researchers who want to acquire a basic mathematical understanding of the most widely used machine learning architectures. Taking the position that learning theory does not exist outside of algorithms that can be run in practice, this book focuses on the theoretical analysis of learning algorithms as it relates to their practical performance. Bach provides the simplest formulations that can be derived from first principles, constructing mathematically rigorous results and proofs without overwhelming students.Provides a balanced and unified treatment of most prevalent machine learning methodsEmphasizes practical application and features only commonly used algorithmic frameworksCovers modern topics not found in existing texts, such as overparameterized models and structured predictionIntegrates coverage of statistical theory, optimization theory, and approximation theoryFocuses on adaptivity, allowing distinctions between various learning techniquesHands-on experiments, illustrative examples, and accompanying code link theoretical guarantees to practical behaviors "The aim of this book is to provide the simplest formulations that can be derived "from first principles" with simple arguments"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780262049443
Stock Image
Learning Theory from First Principles
Seller: Basi6 International, Irving, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEOCT25-277374