Optimization

Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults

Although gradient descent with Polyak's momentum is widely used in modern machine and deep learning, a concrete understanding of its effects on the training trajectory remains …

prin-phunyaphibarn

• Jun 17, 2024 • 1 min read

Fairness

Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold

Proposes a new MMD-based definition of fairness for PCA, then formulate fair PCA as an optimization over the Stiefel manifold. Various theoretical and empirical discussions show …

Junghyun Lee

• Feb 22, 2022 • 1 min read

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Optimization

Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults

Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold