D-IMM: Distributed Iterative Mistake Minimization
As machine learning systems are increasingly deployed on large-scale data, the demand for interpretable and scalable explanation methods has become critical. Existing Explainable AI techniques, particularly for clustering, often struggle with scalability and generalization beyond small, single-node environments. This p...