ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

Understand

Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data.

• The human teacher guides the machine towards accomplishing the task of interest.
• The learning machine leverages big data to find examples that maximize the training value of its interaction with the teacher.
• When the teacher is restricted to labeling examples selected by the machine, this problem is an instance of active learning.