Notice
Herebelow, you can find the tentative schedule of the course.
Date | Lecture | Readings | Deliverables |
2/26 | Introduction | ESL Ch.2 | |
2/28 | Supervised learning | | |
3/4 | PyTorch Tutorial | | HW0 due |
3/6 | Graph neural networks | Lengeling et al., 2021 Daigavane et al., 2021 | |
3/11 | Semi-supervised learning | Yang et al., 2021 | |
3/13 | Semi-supervised learning | | |
3/18 | Self-supervised learning | Balestriero et al., 2023 | HW1 due |
3/20 | Self-supervised learning (+ Project Announcement) | | |
3/25 | Contrastive learning | | |
3/27 | Contrastive learning | | |
4/1 | Multi-task learning | Kendall et al., 2018 | HW2 due |
4/3 | Multi-task learning | Howard et al., 2018 | |
4/8 | Transfer learning & fine-tuning | Kumar et al., 2022 | |
4/10 | Black-box meta learning & in-context learning | Santoro et al., 2016 | |
4/15 | Optimization-based meta-learning | Finn et al., 2017 | HW3 due |
4/17 | Few-shot learning via metric learning | Vinyal et al., 2017 | |
4/22 | Few-shot learning via metric learning | Snell et al., 2017 | |
4/24 | Unsupervised pretraining for few-shot learning (Contrastive) | van den Oord et al., 2019 | |
4/29 | Unsupervised pretraining for few-shot learning (Contrastive) | Chen et al., 2020 | |
5/1 | Unsupervised pretraining for few-shot learning (Generative) | Devlin et al., 2019 | |
5/6 | National Holiday | | HW4 due |
5/8 | Advanced meta-learning topics (task construction) | Yin et al., 2020 | |
5/13 | Variational Inference | Doersch, 2022 | |
5/15 | National Holiday | | |
5/20 | Active learning | Ren et al., 2021 | HW5 due |
5/22 | Active learning | | |
5/27 | Continual learning | Wang et al., 2023 | |
5/29 | Online learning | Hoi et al., 2018 | |
6/3 | Relational reasoning | Santoro et al., 2017 | HW6 due |
6/5 | Intelligence | Chollet, 2019 | |
6/10 | Project presentation | | |
6/12 | | | Report due |
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