Using Classical Algorithms for Modern Applications: MCMC for Tail Calculations, EM - Lecture

Explore classical algorithms applied to modern challenges in this 29-minute lecture from the Computational Genomics Summer Institute. Delve into the use of Markov Chain Monte Carlo (MCMC) for tail probability calculations and Expectation-Maximization (EM) for PET reconstruction. Examine the incorporation of random coincidences in EM-based PET imaging reconstruction and techniques for estimating small tail probabilities using MCMC and Importance Sampling. Gain insights from related research papers, including works on efficient p-value evaluation for resampling-based tests and maximum likelihood reconstruction for emission tomography. Discover how these established methodologies are being adapted and applied to solve contemporary problems in computational genomics and medical imaging.

Saharon Rosset | Using Classical Algorithms for Modern Applications: MCMC for Tail Calculations, EM