In this episode, Dr. Derek Feng drops by to chat about a recent paper on a divide-and-conquer approach (Merged-Averaged Classifiers via Hashing) to massive classification problems. In part 1 (of 2 episodes), we describe the general problem solved by and strategy taken by MACH, wherein the original large classification problem is broken down into smaller-sized classification problems. Next week in the second episode, we talk about more technical details of how the division of labor works, and why it works.
Podden och tillhörande omslagsbild på den här sidan tillhör
Jessi & Susan. Innehållet i podden är skapat av Jessi & Susan och inte av,
eller tillsammans med, Poddtoppen.
