However, TPS focuses only on pixel transformations around the control point, often causing excessive distortion.

In this context, we present a teacher-student framework that can distill the black-box (teacher) model into astudent model with minimal accuracyloss.

Ranking algorithms find extensive usage in diverse areas such as web search, employment,collegeadmission,voting,etc.

This problem is referred to as GP bandits or kernelized bandits .

We study the reinforcement learning problem for discounted Markov Decision Processes(MDPs)underthetabularsetting.

Transformers are central in modern natural language processing and computer vision applications.