Page Rank: Theory and Convergence

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Related lectures (32)

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Continuous-Time Markov Chains: Reversible Chains

Covers Mod.7 on continuous-time Markov chains, focusing on reversible chains and their applications in communication systems.

Continuous-Time Markov Chains: Reversible Chains

Covers continuous-time Markov chains, focusing on reversible chains and their properties.

Equilibrium of Markov Chains

Explores equilibrium in Markov Chains, covering invariant distributions, properties determination, and practical applications.

Eigenvalues and Eigenvectors of Markov Chains

Explores eigenvalues and eigenvectors of Markov chains, focusing on convergence rates and matrix properties.

Continuous-Time Markov Chains: Reversible Chains

Covers reversible continuous-time Markov chains and their properties.

Markov Chains: Introduction and Properties

Covers the introduction and properties of Markov chains, including transition matrices and stochastic processes.

Markov Chains: Convergence and Spectral Gap

Explores Markov chain convergence, spectral gap, and acceleration techniques for faster convergence.

Applied Probability & Stochastic Processes

Covers applied probability, Markov chains, and stochastic processes, including transition matrices, eigenvalues, and communication classes.

Markov Chains: Reversibility & Convergence

Covers Markov chains, focusing on reversibility, convergence, ergodicity, and applications.

Markov Chains: Communicating Classes

Explores communicating classes in Markov chains, distinguishing between transient and recurrent classes, and delves into the properties of these classes.