12 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs
Deepak Narayanan, Keshav Santhanam, Peter Henderson +3
Large language models (LLMs) power many state-of-the-art systems in natural language processing. However, these models are extremely computationally expensive, even at inference ti…
cs.LG2021★ 12 cited
Extending the WILDS Benchmark for Unsupervised Adaptation
Shiori Sagawa, Pang Wei Koh, Tony Lee +17
Machine learning systems deployed in the wild are often trained on a source distribution but deployed on a different target distribution. Unlabeled data can be a powerful point of…
cs.LG2020★ 1 cited
Differentially Private M-band Wavelet-Based Mechanisms in Machine Learning Environments
Kenneth Choi, Tony Lee
In the post-industrial world, data science and analytics have gained paramount importance regarding digital data privacy. Improper methods of establishing privacy for accessible da…