732 citations · 1.3k across the 23 of their papers we have counts for
24 papers
Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events
Matthew B. A. McDermott, Bret Nestor, Peniel Argaw +1
Generative, pre-trained transformers (GPTs, a.k.a. "Foundation Models") have reshaped natural language processing (NLP) through their versatility in diverse downstream tasks. Howev…
Using Machine Learning to Develop Smart Reflex Testing Protocols
Matthew McDermott, Anand Dighe, Peter Szolovits +2
Objective: Reflex testing protocols allow clinical laboratories to perform second line diagnostic tests on existing specimens based on the results of initially ordered tests. Refle…
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…