Abstract:This talk will feature excerpts from my recently published book “Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI”. I’ll cover some of the most exciting
This talk will feature excerpts from my recently published book “Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI”. I’ll cover some of the most exciting problems in Human-in-the-Loop Machine Learning and promising recent advances that address some of these problems. The talk will start with one of the most basic and long-standing questions in machine learning: what are the different ways that we can interpret uncertainty in our models? The talk will then discuss recent advances in transfer learning, including active transfer learning for adaptive sampling and the implications of intermediate task transfer learning on the choice of annotation task and annotation workforce(s). Finally, I will talk about advances in annotation quality control and annotation interfaces, including ways to identify annotators with rare but valid subjective interpretations and human-computer interaction strategies for combining machine learning predictions with human annotations.
What You’ll Learn:
You will learn about how to create good training data for machine learning while also learning about some of the interesting open problems in the fields of active learning and annotation.
Robert Monarch is an expert in combining Human and Machine Intelligence, working with Machine Learning approaches to Text, Speech, Image and Video Processing. Robert has founded several AI companies, building some of the top teams in Artificial Intelligence. He has worked in many diverse environments, from Sierra Leone, Haiti and the Amazon, to London, Sydney and Silicon Valley, in organizations ranging from startups to the United Nations. He has shipped Machine Learning Products at startups and at/with Amazon, Apple, Google, IBM & Microsoft.
Robert has published more than 50 papers on Artificial Intelligence and is a regular speaker about technology in an increasingly connected world. He has a PhD from Stanford University. Robert is the author of Human-in-the-Loop Machine Learning (Manning Publications, 2021)
(Wednesday) 12:10 PM - 12:40 PM