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Advanced algorithms and data structures / Marcello La Rocca

By: Rocca, Marcello La [author]Material type: Text

TextPublication details: Shelter Island, NY : Manning Publications Co., c2021Description: xxvii, 735.pages : illustrations ; 24 cmISBN: 9781617295485Subject(s): ALGORITHMSLOC classification: QA 76.9 .R63 2021

Contents:

1 Introducing data structures -- PART 1 IMPROVING OVER BASIC DATA STRUCTURES -- 2 Improving priority queues: d-way heaps -- 3 Treaps: Using randomization to balance binary search trees -- 4 Bloom filters: Reducing the memory for tracking content -- 5 Disjoint sets: Sub-linear time processing -- 6 Trie, radix trie: Efficient string search -- 7 Use case: LRU cache -- PART 2 MULTIDEMENSIONAL QUERIES -- 8 Nearest neighbors search -- 9 K-d trees: Multidimensional data indexing -- 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval -- 11 Applications of nearest neighbor search -- 12 Clustering -- 13 Parallel clustering: MapReduce and canopy clustering -- PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER -- 14 An introduction to graphs: Finding paths of minimum distance -- 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections -- 16 Gradient descent: Optimization problems (not just) on graphs -- 17 Simulated annealing: Optimization beyond local minima -- 18 Genetic algorithms: Biologically inspired, fast-converging optimization.

Summary: Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You'll discover cutting-edge approaches to a variety of tricky scenarios. You'll even learn to design your own data structures for projects that require a custom solution

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Item type	Current library	Home library	Collection	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	LRC - Main	National University - Manila	Digital Forensic	General Circulation	GC QA 76.9 .R63 2021 (Browse shelf (Opens below))	c.1	Available		NULIB000019528

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Includes index.

1 Introducing data structures --
PART 1 IMPROVING OVER BASIC DATA STRUCTURES --
2 Improving priority queues: d-way heaps --
3 Treaps: Using randomization to balance binary search trees --
4 Bloom filters: Reducing the memory for tracking content --
5 Disjoint sets: Sub-linear time processing --
6 Trie, radix trie: Efficient string search --
7 Use case: LRU cache --
PART 2 MULTIDEMENSIONAL QUERIES --
8 Nearest neighbors search --
9 K-d trees: Multidimensional data indexing --
10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval --
11 Applications of nearest neighbor search --
12 Clustering --
13 Parallel clustering: MapReduce and canopy clustering --
PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER --
14 An introduction to graphs: Finding paths of minimum distance --
15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections --
16 Gradient descent: Optimization problems (not just) on graphs --
17 Simulated annealing: Optimization beyond local minima --
18 Genetic algorithms: Biologically inspired, fast-converging optimization.

Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You'll discover cutting-edge approaches to a variety of tricky scenarios. You'll even learn to design your own data structures for projects that require a custom solution

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