Foundations of Machine Learning / (Record no. 6761)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02225 a2200217 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251010161301.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 251010b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780262039406 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Item number | MohF |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Mohri, Mehryar |
| 245 ## - TITLE STATEMENT | |
| Title | Foundations of Machine Learning / |
| Statement of responsibility, etc | Mehryar Mohri, Afshin Rostamizadeh & Ameet Talwalkar |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | MIT Press : |
| Place of publication | London , |
| Year of publication | ©2018. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xv, 486p. |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE | |
| Title | Adaptive Computation and Machine Learning : |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review.This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine Learning |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Talwalkar, Ameet |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Rostamizadeh, Afshin |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Purchase Price | Bill number | Full call number | Accession Number | Print Price | Bill Date/Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mathematics | Indian Institute of Technology Tirupati | Indian Institute of Technology Tirupati | General Stacks | 07/10/2025 | Shah Book House | 5212.79 | SBH/28599 | 006.3 MohF (12192) | 12192 | 7446.85 | 07/10/2025 | Books |