Algorithms and data structures

Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.

This is the first comprehensive overview of the exciting field of the ''science of science''.

A concise, accessible guide to the modern optimization methods that are transforming computer science, data science, and machine learning.

This book presents fifteen carefully edited expository chapters in the rapidly expanding area of algorithmic graph theory.

This book is an essential guide designed to equip you with the vital tools and knowledge needed to excel in data science.

All the algorithms, proofs, and implementations in Python you need to know for tech job interviews and coding competitions.

This book presents fifteen carefully edited expository chapters in the rapidly expanding area of algorithmic graph theory.

Leading technology scholars examine how networks powered by algorithms are transforming humanity, posing deep questions about power, freedom, and fairness.

All the algorithms, proofs, and implementations in Python you need to know for tech job interviews and coding competitions.

Algorithms will be what we want them to be: we must choose the world we want to live in.

A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.

Leading technology scholars examine how networks powered by algorithms are transforming humanity, posing deep questions about power, freedom, and fairness.

A concise, accessible guide to the modern optimization methods that are transforming computer science, data science, and machine learning.

Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students.

Algorithms will be what we want them to be: we must choose the world we want to live in.

Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students.

Leading international scholars provide comprehensive coverage of the law as it relates to algorithms and artificial intelligence.

This is the first comprehensive overview of the exciting field of the ''science of science''.

A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.

Focuses on the interplay between algorithm design and the underlying computational models.

A sweeping classification theory for computational counting problems using new techniques and theories.

A sweeping classification theory for computational counting problems using new techniques and theories.

This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.

This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.

An easy-to-understand guide covering the key principles of finite element methods and its applications to differential equations.

Helps students transition from problem solving to proving theorems, with a new chapter on number theory and over 150 new exercises.

Helps students transition from problem solving to proving theorems, with a new chapter on number theory and over 150 new exercises.

Presents a new framework for the complexity of algorithms, for all readers interested in the theory of computation.

This groundbreaking, yet accessible book explores the interaction between graph theory and computational complexity using methods from finite model theory.

This groundbreaking, yet accessible book explores the interaction between graph theory and computational complexity using methods from finite model theory.

This comprehensive introduction to algebraic complexity theory presents new techniques for analyzing P vs NP and matrix multiplication.

This comprehensive introduction to algebraic complexity theory presents new techniques for analyzing P vs NP and matrix multiplication.

An extensive and authoritative introduction to property testing, the study of super-fast algorithms for analyzing large quantities of data.

An extensive and authoritative introduction to property testing, the study of super-fast algorithms for analyzing large quantities of data.

This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.

This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.

An overview of the techniques developed to circumvent computational intractability, a key challenge in many areas of computer science.

An overview of the techniques developed to circumvent computational intractability, a key challenge in many areas of computer science.

A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

This book teaches fundamentals of stream processing, covering application design, distributed systems infrastructure, and continuous analytic algorithms.

A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

This book teaches fundamentals of stream processing, covering application design, distributed systems infrastructure, and continuous analytic algorithms.

Lavishly illustrated and entertaining account of the surprising and useful results of the maths of folding and unfolding.

No detailed description available for "e;Building Data-Driven Applications with LlamaIndex"e;.

This book presents a comprehensive study of different tools and techniques available to perform network forensics.

A collection of papers written by prominent experts that examine a variety of advanced topics related to Boolean functions and expressions.

This 1998 book explains the design of geometry algorithms, including discussion of implementation issues and working C code.

This 1998 book explains the design of geometry algorithms, including discussion of implementation issues and working C code.

Now in its third edition, this highly successful textbook is widely regarded as the ''bible of computer algebra''.

Now in its third edition, this highly successful textbook is widely regarded as the ''bible of computer algebra''.