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Alignment of Random Graphs: Informational and Computational Limits - Lecture 2

Offered By: International Centre for Theoretical Sciences via YouTube

Tags

Graph Theory Courses Information Theory Courses Algorithms Courses Computational Complexity Courses Statistical Inference Courses Network Analysis Courses Random Graphs Courses

Course Description

Overview

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Explore the second lecture on "Alignment of Random Graphs: Informational and Computational Limits" delivered by Laurent Massoulié as part of the Data Science: Probabilistic and Optimization Methods discussion meeting. Delve into advanced concepts of graph theory and its applications in data science, focusing on the challenges and limitations of aligning random graphs. Gain insights into both the informational and computational aspects of this complex problem. Benefit from the expertise of a leading researcher in the field as you examine cutting-edge approaches to graph alignment and their implications for various data science applications.

Syllabus

Alignment of Random Graphs: Informational and Computational Limits (Lecture 2) by Laurent Massoulié


Taught by

International Centre for Theoretical Sciences

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