Statistical Learning
Appendices Table of Contents
Other concurrent works address, e.g., learning from soft interventions with polynomial mixing [
Cross-modal Representation Flattening for Multi-modal Domain Generalization Yunfeng Fan
We implement this method by distilling and optimizing generalizable interpolated representations and assigning distinct weights for each modality considering their divergent generalization capabilities.
Training Data Attribution via Approximate Unrolling
Many training data attribution (TDA) methods aim to estimate how a model's behavior would change if one or more data points were removed from the training set.
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers Siyu Chen Department of Statistics and Data Science, Yale University
In particular, most existing work only theoretically explains how the attention mechanism facilitates ICL under certain data models.
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
Classically, sketching has been applied to design low-memory algorithms in the streaming setting, when the input is presented to the algorithm as a sequence of updates.
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
Classically, sketching has been applied to design low-memory algorithms in the streaming setting, when the input is presented to the algorithm as a sequence of updates.
