Lectures related to Submodular Function Minimization

Covers causal broadcast, ensuring messages are delivered in a causal order using algorithms and reliable broadcast.

Covers the concept of property testing using statistical methods.

Explains magnetic induction, force on a dipole, torque, and applications in macroscopic systems.

Explores Locality Sensitive Hashing for nearest neighbor search and submodularity in hash functions.

Covers the von Neumann Extractor, rate computation, and extraction rates.

Covers the properties of entropy and demonstrates their application in data compression.

Explores Cauchy test, generators, and density in functional analysis.

Explores topology, functions, and solutions, emphasizing reduction to Cauchy and uniformization.

Explores Bourgain's theorem on sparsest cut in graphs, emphasizing semimetrics and cut optimization.

Explores linear hatching systems, unique solutions, norms, and fixed points in linear systems.

Explores the calculation of correlation energy and CSF's in electronic structure calculations.

Explores the properties and applications of Cayley graphs in group theory and network analysis.

Covers classical testing of qubits, including measuring in different bases and obtaining uniform results.

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Explores graph theory in brain connectomics, MRI applications, network analysis relevance, and individual fingerprinting.

Explores the concept of symmetry in electric fields and the superposition principle to analyze various charge distributions.

Discusses the two-body problem, center of mass, forces, and Newton's laws.

Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

Covers the Hartree-Fock Roothaan Equations and different types of Hartree-Fock methods, discussing their performance.