Adam
A popular optimization algorithm for training deep learning models, mentioned in the context of hyperparameter tuning.
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Videos Mentioning Adam
Jeremy Howard: fast.ai Deep Learning Courses and Research | Lex Fridman Podcast #35
Lex Fridman
A popular optimization algorithm for training deep learning models, mentioned in the context of hyperparameter tuning.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 2: PyTorch (einops)
Stanford Online
An optimization algorithm that combines momentum and adaptive learning rates, mentioned in contrast to Adagrad and relevant for Assignment 1.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 8: Parallelism
Stanford Online
An optimization algorithm that requires tracking first and second moments of gradients, leading to significant memory overhead.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 9: Scaling Laws
Stanford Online
A common optimization algorithm, discussed in relation to SGD and scaling laws, showing that different optimizers often have similar scaling behaviors.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 11: Scaling Laws
Stanford Online
A standard optimizer that serves as a baseline for comparison with newer algorithms like Muon and is discussed in the context of hyperparameter tuning and scaling.
Stanford CS229 Machine Learning | Spring 2026 | Lecture 3: Weighted Least Squares
Stanford Online
A popular optimizer in machine learning, described as a combination of ideas from second-order methods and momentum.