Learning Optimal Q-functions at the International Conference on Machine Learning 2022
Bojun Huang, Principal Research Scientist at RIT, presented his latest research at the thirty-ninth International Conference on Machine Learning (ICML). The conference was held from July 17-July 23 at the Baltimore Convention Center in Maryland. His paper, Lagrangian Method for Q-Function Learning (with Applications to Machine Translation), was positively accepted among a large pool of submissions.
Addressing optimal-Q function is the focus of his paper. Bojun develops an imitation learning algorithm to demonstrate a possible new approach to Q-function learning by applying a lagrangian method. Lagrangian Method for Q-Function Learning (with Applications to Machine Translation) can be read in its entirety here.
The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning.
ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics.
ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students.