Expert Aggregation

Expert aggregation focuses on combining predictions from multiple specialized models ("experts") to improve overall accuracy and efficiency, addressing limitations of single-model approaches. Current research explores diverse architectures like Mixture of Experts (MoE), including heterogeneous and nested variations, and employs algorithms such as deep reinforcement learning and online aggregation methods like Bernstein Online Aggregation (BOA) to effectively weigh and integrate expert outputs. This field is significant for enhancing performance in various applications, from natural language processing and computer vision to financial forecasting and multimodal data analysis, by leveraging the strengths of multiple models while mitigating individual weaknesses.