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Concept

Distance (graph theory)

Related lectures (32)

Networked Control Systems: Opportunities

Explores coordination in networked control systems, graph theory, and consensus algorithms.

Consensus Algorithms: Weight Assignment and Applications

Explores the design of graph weights for consensus and applications in sensor networks.

Consensus in Networked Control Systems

Explores consensus in networked control systems through graph weight design and matrix properties.

Graph Theory: Path Weighted by Amplitude

Covers the calculation of paths in a graph, focusing on amplitude-weighted paths.

Networks, Flows MOOC: Optimization: principles and algorithms - Network and discrete optimization

Covers the definition of flow in a network and flow calculation.

Non-parametric regression for networks

Explores non-parametric regression for networks, covering object data analysis, network graphs, extrinsic distances, and practical projections.

Minimum Guardians in Graphs

Explores the concept of minimizing guardians in graphs through strategic edge selection.

Subgraphs vs Induced Subgraphs

Distinguishes between subgraphs and induced subgraphs in graph theory, illustrating the construction of minimal spanning trees.

Probabilistic method and its applications

Introduces the probabilistic method to prove existence results in graph theory.

Stochastic Block Model

Covers the Stochastic Block Model and its application in community detection, exploring its mathematical formulation and challenges.

Unweighted Bipartite Matching

Introduces unweighted bipartite matching and its solution using linear programming and the simplex method.

Geometry: Eulerian Circuits

Explores Eulerian circuits through the Königsberg bridges problem, leading to the development of graph theory and topology.

Belief Propagation for Graph Coloring

Explores Belief Propagation for graph coloring and its convergence properties.

Topology in Complex Networks: Insights from Topological Data Analysis

Explores the role of higher-order topological properties in complex networks using topological data analysis for structural break and price anomaly detection.

Dynamic Programming: Shortest Paths Algorithms

Explores dynamic programming strategies for finding shortest paths in networks with various algorithms and complexities.

Cavity Method: Mean Field Theory

Explores the Cavity Method in Mean Field Theory, analyzing spins in an external field within a graph.

Polynomial Identity Testing

Covers polynomial identity testing using oracles and random point evaluation, with applications in graph theory and algorithmic aspects.

Distances and Motif Counts Log in to Mediaspace to watch this video

Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.

Convergence of Random Walks Log in to Mediaspace to watch this video

Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.

Embedding Graphs into Trees Log in to Mediaspace to watch this video

Covers embedding graphs into trees with a focus on minimizing distortion and Bartal Tree embeddings.