Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search ...

Graphs -- data structures that show the relationship among objects -- are highly versatile. It's easy to imagine a graph depicting a social media network's web of connections.

The release of Memgraph 2.0 allows developers to feed algorithms such as PageRank, Community Detection, Breadth-First Search, which is a model for searching a tree data structure for nodes that ...

Specialization: Foundations of Data Structures and Algorithms Instructor: Dr. Sriram Sankaranarayanan, Professor of Computer Science Prior knowledge needed: You must understand all concepts covered in ...

Tour of the most important data structures, fundamental algorithms, and algorithm design techniques: lists, stacks, queues, dynamic arrays, hash tables, heaps, priority queues, disjoint set unions, ...

Design algorithms and analyze their complexity in terms of running time and space usage; Create applications that are supported by highly efficient algorithms and data structures for the task at hand; ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.

Definition of a Data Structure & Algorithms. Data structures and algorithms are vital elements in many computing applications. When programmers design and build applications, they need to model ...