[Free Live] The process of developing an AI competition-winning algorithm into an oral presentation paper for an international conference

This program is intended for developers, data scientists, AI/ML researchers, and graduate students who are participating in AI competitions or wish to develop ideas gained from competitions into actual research and papers. Starting with the time-series forecasting algorithm used to win 3rd place in the K League-University of Seoul Open AI Competition (which featured 947 participating teams), we will share the actual research process—from problem analysis and algorithm design to performance improvement, research idea derivation, and paper writing. In particular, we will go beyond simply achieving good results in a competition. We will introduce a case-centered approach on how we identified the limitations of the winning algorithm, evolved it into a new algorithm called FS-DCM, and eventually developed it into an Oral paper for the Methods Track at the International Conference on Automated Machine Learning (AutoML Conference 2024). Through the entire workflow of "Competition → Winning Algorithm → Research Idea → Algorithm Advancement → Paper → International Conference Oral," we will explore how to connect AI competition experiences to actual research achievements.