YoVDO

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

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
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

Related Courses

Теория вероятностей для начинающих
Moscow Institute of Physics and Technology via Coursera
Universality of Random Graphs - Gal Kronenberg
Institute for Advanced Study via YouTube
The Science of Networks - C4 Public Lectures
Santa Fe Institute via YouTube
Optimization of the Sherrington-Kirkpatrick Hamiltonian
IEEE via YouTube
Fast Uniform Generation of Random Graphs with Given Degree Sequences
IEEE via YouTube