Yaoliang Yu

Additive Approximations in High Dimensional Nonparametric Regression via the SALSA

2016 · arXiv (Cornell University)

High dimensional nonparametric regression is an inherently difficult problem with known lower bounds depending exponentially in dimension. A popular strategy to alleviate this curse of dimensionality has been to use additive models of \emph{first order}, …

Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors

2024

Machine learning models have achieved great success in supervised learning tasks for end-to-end training, which requires a large amount of labeled data that is not always feasible. Recently, many practitioners have shifted to self-supervised learning …

DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

2020

Large-scale pre-trained language models such as BERT have brought significant improvements to NLP applications. However, they are also notorious for being slow in inference, which makes them difficult to deploy in realtime applications. We propose …