Samory Kpotufe

In this engaging conversation, Samory Kpotufe, an associate professor at Columbia University, delves into the complexities of adaptive algorithms in machine learning. He highlights the importance of self-tuning algorithms that can adjust to varying data. The discussion covers transfer learning, emphasizing practical applications and challenges. Samory also touches on innovative methods in unsupervised learning and anomaly detection, especially within resource-constrained devices. His insights into the intersection of fractals and high-dimensional data add a fascinating layer to the conversation.