Statistical Learning
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms SUPPLEMENTARY DOCUMENT
In Section S1, we provide additional background on dimension theory.
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
Understanding generalization in deep learning has been one of the major challenges in statistical learning theory over the last decade.
Learning Models for Actionable Recourse Alexis Ross
Explanations are important not only to ensure that there are no issues with the way the prediction is made (e.g., making sure the decision is free of
Identifying Mislabeled Data using the Area Under the Margin Ranking
Our goal is to automatically identify and subsequently remove mislabeled samples from training datasets. Discarding these harmful data will reduce memorization and improve generalization.
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection
In this paper, we present a method for accelerating and structuring self-attentions: Sparse Adaptive Connection (SAC).