Lloyd Algorithm

The Lloyd algorithm, a fundamental clustering technique, aims to partition data points into groups minimizing within-group variance. Current research focuses on extending its applicability to diverse data types (e.g., matrices, time series) and problem settings (e.g., online learning, hierarchical forecasting), often incorporating it within larger frameworks like low-rank mixture models or rule-based systems for multi-robot control. These advancements improve efficiency, robustness, and the algorithm's ability to handle complex scenarios, impacting fields such as image processing, speech recognition, and robotics.