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CS-330 Lecture 4: Optimization-Based Meta-Learning
This lecture is part of the CS-330 Deep Multi-Task and Meta Learning course, taught by Chelsea Finn in Fall 2023 at Stanford. The goal of this lecture is to understand the basics of optimization-based meta learning techniques. You will also learn about the trade-offs between black-box and optimization-based meta learning!
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CS-330 Lecture 3: Black-Box Meta-Learning & In-Context Learning
This lecture is part of the CS-330 Deep Multi-Task and Meta Learning course, taught by Chelsea Finn in Fall 2023 at Stanford. The goal of this lecture is to learn how to implement black-box meta-learning techniques. We will also talk about a case study of GPT-3!
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CS-330 Lecture 2: Transfer Learning and Meta-Learning
This lecture is part of the CS-330 Deep Multi-Task and Meta Learning course, taught by Chelsea Finn in Fall 2023 at Stanford. The goal of this lecture is to learn how to transfer knowledge from one task to another, discuss what it means for two tasks to share a common structure, and start thinking about meta learning.
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CS-330 Lecture 1: Multi-Task Learning
This is the first lecture of the CS-330 Deep Multi-Task and Meta Learning course, taught by Chelsea Finn in Fall 2023 at Stanford. The goal of this lecture is to understand the key design decisions when building multi-task learning systems.
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CS-330: Deep Multi-Task and Meta Learning - Introduction
I have been incredibly interested in the recent wave of multimodal foundation models, especially in robotics and sequential decision-making. Since I never had a formal introduction to this topic, I decided to audit the Deep Multi-Task and Meta Learning course, which is taught yearly by Chelsea Finn at Stanford. I will mainly document my takes on the lectures, hopefully making it a nice read for people who would like to learn more about this topic!