The PDF covers the following
topics related to Computer Algorithms : Discrete Algorithms, Minimum
Spanning Trees, Arborescences: Directed Spanning Trees, Dynamic
Algorithms for Graph Connectivity, Shortest Paths in Graphs,
Low-Stretch Spanning Trees, Graph Matchings I: Combinatorial
Algorithms, Graph Matchings II: Weighted Matchings, Graph Matchings
III: Algebraic Algorithms, The Curse of Dimensionality, and
Dimension Reduction, Dimension Reduction and the JL Lemma, Streaming
Algorithms, Dimension Reduction: Singular Value Decompositions, From
Discrete to Continuous Algorithms, Online Learning: Experts and
Bandits, Solving Linear Programs using Experts, Approximate
Max-Flows using Experts, The Gradient Descent Framework, Mirror
Descent, The Centroid and Ellipsoid Algorithms, Interior-Point
Methods, Combating Intractability, Approximation Algorithms via SDPs,
Online Algorithms, Additional Topics, Prophets and Secretaries.
covers the following topics: Algorithm Analysis, algorithmic patterns, Standard
I/O and iostream, Foundational Data Structures and Basic Abstract Data Types,
Linked-list, Stacks and Queues, PA1 walkthrough, Pointer, Hashing, Recursion and
Recurrence Relations, Trees, Binary Search Trees, Range and Multidimensional
Searches, Heaps, Tries, Balanced Search Trees, Binary-tree Representations of
The field of approximation algorithms has
developed in response to the difficulty in solving a good many optimization
problems exactly. This note will present general techniques that underly these
This note concentrates
on the design of algorithms and the rigorous analysis of their efficiency.
Topics covered includes: the basic definitions of algorithmic complexity, basic
tools such as dynamic programming, sorting, searching, and selection; advanced
data structures and their applications, graph algorithms and searching
techniques such as minimum spanning trees, depth-first search, shortest paths,
design of online algorithms and competitive analysis.
This note will cover
classic and modern algorithmic ideas that are central to many areas of Computer
Science. The focus is on most powerful paradigms and techniques of how to design
algorithms, and measure their efficiency. The topics will include hashing,
sketching, dimension reduction, linear programming, spectral graph theory,
gradient descent, multiplicative weights, compressed sensing, and others.
This note covers the following topics:
Algorithms and Data Structures, Introduction to Java, Software Development,
Writing Classes, Writing Classes in Java, Unit Testing, Building Large Java
Applications, Inheritance and Polymorphism, Interfaces, A Math Review, Algorithm
Analysis, Data Types versus Data Structures, Collections, Stacks ,Queues, Lists,
Recursion, Sorting, Trees, Oriented Trees, Ordered Trees, Binary Trees, Sets and
Dictionaries, Search Trees, Binary Search Trees, Red-Black Trees.
note covers the following topics related to Algorithm Analysis and Design: Model
and Analysis, Warm up problems, Brute force and Greedy strategy, Dynamic
Programming, Searching, Multidimensional Searching and Geometric algorithms,
Fast Fourier Transform and Applictions, String matching and finger printing,
Graph Algorithms, NP Completeness and Approximation Algorithms.
The material of this book is aimed at advanced
undergraduate information (or computer) science students,
postgraduate library science students, and research workers in the
field of IR. Some of the chapters, particular chapter 6, make simple
use of a little advanced mathematics.