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A Bayesian Approach to Data Compression

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Joe Suzuki
Joe Suzuki

This document outlines a two-part course on Bayesian approaches to data compression. Part I on July 17th will cover data compression for known and unknown sources over 90 minutes, including a 45-minute exercise. Part II on July 24th will focus on learning graphical models from data based on the concepts from Part I.

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A Bayesian Approach to Data Compression Joe Suzuki July 17, 2017
Road Map PART-I: July 17, 2017 1. Data Compression for Known Source (30 mins) 2. Data Compression for Unknown Source (15 mins) 3. Exercise (45 mins) PART-II: July 24, 2017 Learning a graphical model from data (based on PART-I)
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression
A Bayesian Approach to Data Compression

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A Bayesian Approach to Data Compression

  • 1. A Bayesian Approach to Data Compression Joe Suzuki July 17, 2017
  • 2. Road Map PART-I: July 17, 2017 1. Data Compression for Known Source (30 mins) 2. Data Compression for Unknown Source (15 mins) 3. Exercise (45 mins) PART-II: July 24, 2017 Learning a graphical model from data (based on PART-I)