Search

Skip to Search Results
  • Spring 2022

    Konobeev, Mikhail

    A key problem in the theory of meta-learning is to understand how the task distributions influence transfer risk, the expected error of a meta-learner on a new task drawn from the unknown task distribution. In this work, focusing on fixed design linear regression with Gaussian noise and a...

  • Fall 2023

    Saleh, Esraa M M

    Learning only by direct interaction with the world can be expensive in many real world applications. In such settings, Model-based Reinforcement Learning (MBRL) methods are a promising avenue towards data-efficiency. By planning with a model, a sequential decision making agent can decrease its...

1 - 2 of 2