Mining Social Graphs

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Related lectures (27)

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Fixed Points in Graph Theory

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Statistical Analysis of Network Data: Structures and Models

Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.

Algorithmic Paradigms for Dynamic Graph Problems

Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.

Epidemic Spreading Models

Covers classical models of epidemic spreading and dynamics on networks with examples.

Modular Programming: Managing Project Complexity

Covers modular programming principles, focusing on managing project complexity through effective code structuring and dependency management.

Handling Networks: Graph Theory

Explores graph theory concepts, centrality measures, and real-world network properties, providing insights into handling diverse types of networks.

Linear Algebra: Matrices and Linear Applications

Covers matrices, linear applications, vector spaces, and bijective functions.

Graph Algorithms: Modeling and Traversal

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Handling Network Data

Covers handling network data, types of graphs, centrality measures, and properties of real-world networks.

Graph Algorithms: Basics

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.