This year, Long Beach, Calif. will host the Thirty-Sixth International Conference on Machine Learning (ICML). The conference is the premier gathering for artificial intelligence (AI) professionals who specialize in the branch of AI known as machine learning.
Georgia Tech researchers will present 18 research papers at this year’s event. The papers touch on a variety of aspects of machine learning including blended unconditional gradients, clustering with fairness constraints, and observational agents.
School of Interactive Computing assistant professor, Byron Boots is a 2019 area chair. Boots is also the co-organizer of the Real-World Sequential Decision Making: Reinforcement Learning and Beyond workshop and a guest speaker at the Generative Modeling and Model-Based Reasoning for Robotics and AI.
“ICML is globally renowned as one of the best conferences for machine learning research. Year after year, cutting edge research is presented and published and it’s a sign of ML@GT’s strength that Georgia Tech is consistently a top contributor in the accepted papers.” Justin Romberg, School of Electrical and Computer Engineering Schlumberger Professor and associate director of the Machine Learning Center at Georgia Tech (ML@GT).
Hosted June 9 through 15 at the Long Beach Convention and Entertainment Center, ICML is one of the fastest growing conferences in the world. It will bring together over 8,000 participants including entrepreneurs, engineers, graduate students, postdocs, and academic and industrial researchers.
Along with Georgia Tech papers, other accepted papers will include work in closely related fields like statistics, data science, and artificial intelligence, and important application areas like speech recognition, robotics, and machine vision.
For a full list of Georgia Tech’s research papers and more information about Georgia Tech’s presence at the conference, please click here.