732 citations · 1.3k across the 23 of their papers we have counts for
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A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021
Fabian Falck, Yuyin Zhou, Emma Rocheteau +7
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. This index is not complete, as some accepted abstracts chose to opt-out of inclusi…
Meta-Learning to Improve Pre-Training
Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith +2
Pre-training (PT) followed by fine-tuning (FT) is an effective method for training neural networks, and has led to significant performance improvements in many domains. PT can inco…
Parkinsonian Chinese Speech Analysis towards Automatic Classification of Parkinson's Disease
Hao Fang, Chen Gong, Chen Zhang +2
Speech disorders often occur at the early stage of Parkinson's disease (PD). The speech impairments could be indicators of the disorder for early diagnosis, while motor symptoms ar…
Structure Inducing Pre-Training
Matthew B. A. McDermott, Brendan Yap, Peter Szolovits +1
Language model pre-training and derived methods are incredibly impactful in machine learning. However, there remains considerable uncertainty on exactly why pre-training helps impr…
Adversarial Contrastive Pre-training for Protein Sequences
Matthew B. A. McDermott, Brendan Yap, Harry Hsu +2
Recent developments in Natural Language Processing (NLP) demonstrate that large-scale, self-supervised pre-training can be extremely beneficial for downstream tasks. These ideas ha…