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Related lectures (29)

Page 3 of 3

Graph Algorithms: Basics

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

Physarum can compute shortest paths

Explores how Physarum Polycephalum can compute shortest paths in a directed graph model.

Linearity of Expectation: First Moment Method

Introduces Linearity of Expectation and the First Moment Method, explores probability theory problems like Buffon's Needle, and discusses transitive tournaments and Ham paths.

Graph Algorithms: Modeling and Representation

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Approximate Inference Algorithm

Covers the Chow-Liu algorithm for approximate inference and optimal tree approximation.

Decentralized ML: Collaborative Training & Causal Influence Structure

Explores collaborative training in decentralized ML and causal influence structure discovery.

Information Retrieval Indexing: Part 2

Explores constructing an inverted file for information retrieval indexing and the map-reduce programming model.

Graph Theory in Neural Signal Processing

Explores neural signal processing through graph theory, multivariate methods, and fMRI analysis.

Robust and Scalable Systems

Covers the instructor's work on designing, building, scaling, and ensuring the robustness of operating systems during their PhD.