Gentle Introduction
"Gentle Introduction" papers encompass introductory materials across diverse areas of machine learning and artificial intelligence, aiming to provide accessible entry points for researchers and practitioners. Current research focuses on explaining complex models (e.g., transformers, diffusion models), developing new algorithms for specific tasks (e.g., reinforcement learning, bi-level optimization), and addressing challenges in data handling (e.g., non-IID data in federated learning, data augmentation for singing voice synthesis). These introductory works are crucial for broadening participation in the field and facilitating the application of advanced AI techniques to various domains, including healthcare, robotics, and natural language processing.
Papers
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning
Yihua Zhang, Prashant Khanduri, Ioannis Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
Data Collaboration Analysis applied to Compound Datasets and the Introduction of Projection data to Non-IID settings
Akihiro Mizoguchi, Anna Bogdanova, Akira Imakura, Tetsuya Sakurai