Notes on Randomized Algorithms
eBook | Free |
Rating | |
Author | James Aspnes |
Publisher | Self-publishing |
Published | 2020 |
Pages | 459 |
Language | English |
Format | Paper book / ebook (PDF) |
Lecture notes for the Yale Computer Science course CPSC 469/569 Randomized Algorithms. Suitable for use as a supplementary text for an introductory graduate or advanced undergraduate course on randomized algorithms. Discusses tools from probability theory, including random variables and expectations, union bound arguments, concentration bounds, applications of martingales and Markov chains, and the Lovasz Local Lemma. Algorithmic topics include analysis of classic randomized algorithms such as Quicksort and Hoare's FIND, randomized tree data structures, hashing, Markov chain Monte Carlo sampling, randomized approximate counting, derandomization, quantum computing, and some examples of randomized distributed algorithms.
- James Aspnes
Similar Books
Pro Machine Learning Algorithms
by Kishore Ayyadevara
Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so that you get a ...
Price: $37.99 | Publisher: Apress | Release: 2018
by Magnus Lie Hetland
Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.The book is intended for Python programmers who need...
Price: $18.00 | Publisher: Apress | Release: 2010
Python Algorithms, 2nd Edition
by Magnus Lie Hetland
Python Algorithms, 2nd Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.The book deals with some of the most im...
Price: $33.75 | Publisher: Apress | Release: 2014
Algorithmic Aspects of Machine Learning
by Ankur Moitra
This course is organized around algorithmic issues that arise in machine learning. Modern machine learning systems are often built on top of algorithms that do not have provable guarantees, and it is the subject of debate when and why they work. In this class, we focus on designing algorithms whose performance we can rigorously analyze fo...
Free ebook | Publisher: Self-publishing | Release: 2018
SQL: A Beginner's Guide, 3rd Edition
by Andy Oppel, Robert Sheldon
Written to the SQL:2006 ANSI/ISO standard, this easy-to-follow guide will get you started programming in SQL right away. You will learn how to retrieve, insert, update, and delete database data, and perform management and administrative functions. SQL: A Beginner's Guide, Third Edition covers new features, including SQL/XML, and is l...
Price: $3.65 | Publisher: McGraw-Hill | Release: 2008
Pervasive Computing and Networking
by Mohammad S. Obaidat, Mieso Denko, Isaac Woungang
This book presents state-of-the-art research on architectures, algorithms, protocols and applications in pervasive computing and networks.With the widespread availability of wireless and mobile networking technologies and the expected convergence of ubiquitous computing with these emerging technologies in the near future, pervasive comput...
Price: $84.29 | Publisher: Wiley | Release: 2011
by Clay Breshears
If you're looking to take full advantage of multi-core processors with concurrent programming, this practical book provides the knowledge and hands-on experience you need. The Art of Concurrency is one of the few resources to focus on implementing algorithms in the shared-memory model of multi-core processors, rather than just theore...
Price: $30.14 | Publisher: O'Reilly Media | Release: 2009
Deep Learning for Natural Language Processing
by Palash Goyal, Sumit Pandey, Karan Jain
Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.You'll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP...
Price: $31.93 | Publisher: Apress | Release: 2018