"Explainable Clustering: Interpretable and Reliable Learning" – Liren Shan, Research at TTIC скачать в хорошем качестве

"Explainable Clustering: Interpretable and Reliable Learning" – Liren Shan, Research at TTIC

“Explainable Clustering: Interpretable and Reliable Learning” Liren Shan, TTIC Originally recorded on December 5, 2025, at TTIC. In this talk, Liren Shan studies explainable k-medians and k-means clustering via threshold decision trees that produce interpretable cluster assignments. They present new algorithms that achieve good (bi-criteria) approximations to optimal unconstrained clustering, and discuss broader principles for designing machine learning methods that are both interpretable and reliable. Timestamps: 00:00 Introduction 01:20 Talk begins 53:10 Q&A #ExplainableAI #Clustering #InterpretableML #ReliableAI #KMeans #Kmedians #MachineLearning #Theory #Algorithms #Research #TTIC