Machine Learning to Present Seven Papers at Prestigious Deep Learning Conference

Researchers from the Machine Learning Center at Georgia Tech (ML@GT) will present seven papers at the Ninth Annual International Conference on Learning Representations (ICLR). Accepted research will present new findings on topics such as increasing multi-platform deployment and semi-supervised object detection.

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ML@GT Associate Director and School of Interactive Computing (IC) Assistant Professor Zsolt Kira and Tuo Zhou, an assistant professor in the H. Milton Stewart School of Industrial Systems and Engineering will serve as conference area chairs. IC Associate Professor Devi Parikh and School of Computational Science and Engineering Associate Professor Polo Chau are steering committee members of the Rethinking ML Papers workshop.

The workshop will focus on answering questions like how to design an inclusive publication format for ML research, how to communicate ML research and theory more effectively, and how best to interpret complex information in a visual setting.

“ML@GT continues to publish cutting-edge research across many fields. We are looking forward to sharing this recent work at a venue as well regarded as ICLR,” said Kira.

Accepted papers from Georgia Tech are:

[RELATED: Watch short summaries of accepted papers]

ICLR is dedicated to advancing deep learning and publishing cutting-edge research that impacts data science, artificial intelligence, and statistics. The conference will be held virtually May 3-7.

Story by Allie McFadden, Communications Officer,

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