Search Results for author: Harry Hochheiser

Found 6 papers, 1 papers with code

Online Transfer Learning for RSV Case Detection

no code implementations3 Feb 2024 Yiming Sun, Yuhe Gao, Runxue Bao, Gregory F. Cooper, Jessi Espino, Harry Hochheiser, Marian G. Michaels, John M. Aronis, Ye Ye

To address this challenge, we introduce Predictive Volume-Adaptive Weighting (PVAW), a novel online multi-source transfer learning method.

Transfer Learning

Definition drives design: Disability models and mechanisms of bias in AI technologies

no code implementations16 Jun 2022 Denis Newman-Griffis, Jessica Sage Rauchberg, Rahaf Alharbi, Louise Hickman, Harry Hochheiser

The increasing deployment of artificial intelligence (AI) tools to inform decision making across diverse areas including healthcare, employment, social benefits, and government policy, presents a serious risk for disabled people, who have been shown to face bias in AI implementations.

Decision Making

Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research

no code implementations NAACL 2021 Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé, Harry Hochheiser

Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings.

TextEssence: A Tool for Interactive Analysis of Semantic Shifts Between Corpora

1 code implementation NAACL 2021 Denis Newman-Griffis, Venkatesh Sivaraman, Adam Perer, Eric Fosler-Lussier, Harry Hochheiser

Embeddings of words and concepts capture syntactic and semantic regularities of language; however, they have seen limited use as tools to study characteristics of different corpora and how they relate to one another.

An Interactive Tool for Natural Language Processing on Clinical Text

no code implementations6 Jul 2017 Gaurav Trivedi, Phuong Pham, Wendy Chapman, Rebecca Hwa, Janyce Wiebe, Harry Hochheiser

Natural Language Processing (NLP) systems often make use of machine learning techniques that are unfamiliar to end-users who are interested in analyzing clinical records.

BIG-bench Machine Learning

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