Huffman Coding Based Encoding Techniques for Fast Distributed Deep Learning | Proceedings of the 1st Workshop on Distributed Machine Learning

Huffman Coding

Understanding the Huffman coding procedures in digital communication with examples

a) Use Huffman coding to encode these symbols with frequencies a: 0.4, b: 0.2, c: 0.2, d: 0.1, e: 0.1 in two different ways by breaking ties in the algorithm differently. First, among the trees of minimum weight select two trees with the largest number of vertices to combine at each stage of the algorithm. Second, among the trees of minimum weight select two trees with the smallest number of vertices at each stage. b) Compute the average number of bits required to encode a symbol with each code