( Note: below schedule is subject to changes as the course progresses )
Aug
12 Introduction & motivation for Meta-learning
14 Numerai challenge & discussion
19 Recap of deep-learning in the context of Numerai; Assignment 1 starts
21 ARC challenge & discussion of "Measure of Intelligence" paper
28 Meta-learning formulation & metric-based meta-learning
31 Matching Networks
Sep
2 Model-based meta-learning (CNP)
4 Optimization-based meta-learning (MAML)
9 Neuro-symbolic learning, inference-time search and ARC as a program synthesis problem; Assignment 2 starts
11 Overview of generative AI and LLMs as model-based meta-learners
18 Advanced meta-learning papers 1; Quiz 1
23 Neuro-symbolic program synthesis papers 1
25 Advanced meta-learning papers 2
30 Advanced meta-learning papers 3
Oct
3-11 Mid-terms
14 Neuro-symbolic program synthesis papers 2
16 Discussion & Tutorial on Assignment 1
21 LLMs and meta-learning; Test-time adaptation
23 Discussion & Tutorial on Assignment 2; Quiz 2
28-2 Break
Nov
4 Advanced meta-learning papers 4
6 Neuro-symbolic program synthesis papers 4
10 (EOD) Assignment 1 is due
11 Student presentations on Assignment 1
13 Student presentations on Assignment 1 (continued)
17 (EOD) Assignment 2 is due
18 Student presentations on Assignment 2
20 Student presentations on Assignment 2 (continued)
25 Applying meta-learning discussion: e.g. Hebbian test-time adaptation & Quiz 3;
27 Course summary & applying meta-learning in practical scenarios.
Dec
11 Final Exam