Ksenia Konyushkova Interview – Learning Active Learning from Data

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Ksenia Konyushkova Interview - Learning Active Learning from Data

In this episode, I speak with Ksenia Konyushkova, Ph.D. student in the CVLab at Ecole Polytechnique Federale de Lausanne in Switzerland.

Ksenia and I connected at NIPS in December to discuss her interesting research into ways we might apply machine learning to ease the challenge of creating labeled datasets for machine learning. The first paper we discuss is “Learning Active Learning from Data,” which suggests a data-driven approach to active learning that trains a secondary model to identify the unlabeled data points which, when labeled, would likely have the greatest impact on our primary model’s performance. We also discuss her paper “Learning Intelligent Dialogs for Bounding Box Annotation,” in which she trains an agent to guide the actions of a human annotator to more quickly produce bounding boxes.

TWiML Online Meetup Update

Join us Tuesday, March 13th for the March edition of the Online Meetup! Sean Devlin will be doing an in-depth review of reinforcement learning and presenting the Google DeepMind paper, “Playing Atari with Deep Reinforcement Learning.” Head over to twimlai.com/meetup to learn more or register.

Conference Update

Be sure to check out some of the great names that will be at the AI Conference in New York, Apr 29–May 2, where you’ll join the leading minds in AI, Peter Norvig, George Church, Olga Russakovsky, Manuela Veloso, and Zoubin Ghahramani. Explore AI’s latest developments, separate what’s hype and what’s really game-changing, and learn how to apply AI in your organization right now. Save 20% on most passes with discount code PCTWIML. Early price ends February 2!

The notes for this show can be found at https://twimlai.com/talk/116.

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