Vowpal Wabbit 8.5.0 & NIPS tutorial

Vowpal Wabbit 8.5.0 & NIPS tutorial Yesterday, I tagged VW version 8.5.0 which has many interactive learning improvements (both contextual bandit and active learning), better support for sparse models, and a new baseline reduction which I’m considering making a part of the default update rule. If you want to know the details, we’ll be doing a mini-tutorial during the Friday lunch break at the Extreme Classification workshop at NIPS. Please join us if interested.
Original Post: Vowpal Wabbit 8.5.0 & NIPS tutorial

The Multiworld Testing Decision Service

The Multiworld Testing Decision Service We made a tool that you can use. It is the first general purpose reinforcement-based learning system Reinforcement learning is much discussed these days with successes like AlphaGo. Wouldn’t it be great if Reinforcement Learning algorithms could easily be used to solve all reinforcement learning problems? But there is a well-known problem: It’s very easy…
Original Post: The Multiworld Testing Decision Service

Randomized experimentation

One good thing about doing machine learning at present is that people actually use it! The back-ends of many systems we interact with on a daily basis are driven by machine learning. In most such systems, as users interact with the system, it is natural for the system designer to wish to optimize the models under the hood over time,…
Original post: Randomized experimentation
Source: Machine Learning (Theory)