2 papers
cs.LG2026
Grokking in Linear Models for Logistic Regression
Nataraj Das, Atreya Vedantam, Chandrashekar Lakshminarayanan
Grokking, the phenomenon of delayed generalization, is often attributed to the depth and compositional structure of deep neural networks. We study grokking in one of the simplest p…
cs.AI2026
Learning to Price: Interpretable Attribute-Level Models for Dynamic Markets
Srividhya Sethuraman, Chandrashekar Lakshminarayanan
Dynamic pricing in high-dimensional markets poses fundamental challenges of scalability, uncertainty, and interpretability. Existing low-rank bandit formulations learn efficiently…