#49: Extreme Classification: Going at MACH Speed (Part 1)
Description
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. --- Send in a voice message: https://anchor.fm/databytes/message Support this podcast: https://anchor.fm/databytes/support
The podcast DataBytes is embedded on this page from an open RSS feed. All files, descriptions, artwork and other metadata from the RSS-feed is the property of the podcast owner and not affiliated with or validated by Podplay.