Zobrazeno 1 - 10
of 30
pro vyhledávání: '"James R. Foulds"'
Publikováno v:
Computational Linguistics, Vol 48, Iss 4 (2022)
We propose a method that uses neural embeddings to improve the performance of any given LDA-style topic model. Our method, called neural embedding allocation (NEA), deconstructs topic models (LDA or otherwise) into interpretable vector-space embeddin
Externí odkaz:
https://doaj.org/article/4f518a22b5844cf6895a7258e5b704a9
Publikováno v:
Entropy, Vol 25, Iss 4, p 660 (2023)
We propose definitions of fairness in machine learning and artificial intelligence systems that are informed by the framework of intersectionality, a critical lens from the legal, social science, and humanities literature which analyzes how interlock
Externí odkaz:
https://doaj.org/article/489c8d9df7da43b0b6778f81880cd4d5
Publikováno v:
Journal of Psychiatric and Mental Health Nursing. 28:924-939
WHAT IS KNOWN ON THE SUBJECT?: Aggression and violence are persistent problems in psychiatric inpatient units. Violence preventive factors have been identified from both staff's and patients' perspectives. Violent and aggressive inpatient incidents h
Publikováno v:
Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20)
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Journal of Artificial Intelligence Research
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Journal of Artificial Intelligence Research
Many applications of Bayesian data analysis involve sensitive information, motivating methods which ensure that privacy is protected. We introduce a general privacy-preserving framework for Variational Bayes (VB), a widely used optimization-based Bay
Autor:
James T. Morton, Nicholas A. Bokulich, Rob Knight, Se Jin Song, Trent R. Northen, Tami L. Swenson, Richard Bonneau, Louis-Félix Nothias, Mingxun Wang, Robert A. Quinn, Michelle H. Badri, Pieter C. Dorrestein, Aaron Watters, Alexander A. Aksenov, Marc W. Van Goethem, James R. Foulds, Yoshiki Vázquez-Baeza
Publikováno v:
Nature Methods. 16:1306-1314
Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estim
Autor:
Rebecca McKetin, Craig Cumming, Michael Farrell, Emily Stockings, Janni Leung, Grant Sara, Julia Lappin, Yan Huo, James R. Foulds, Jesse T Young, Shalini Arunogiri, Louisa Degenhardt
Publikováno v:
EClinicalMedicine
EClinicalMedicine, Vol 16, Iss, Pp 81-97 (2019)
EClinicalMedicine, Vol 16, Iss, Pp 81-97 (2019)
Background: The use of amphetamines is a global public health concern. We summarise global data on use of amphetamines and mental health outcomes. Methods: A systematic review and meta-analysis (CRD 42017081893). We searched Medline, EMBASE, PsycInfo
Publikováno v:
Current opinion in psychiatry. 35(1)
PURPOSE OF REVIEW This review examines the prevalence of personality disorder in those with mental state disorder. Some challenges disentangling these psychopathologies are delineated and advances in understanding broadly are reviewed. RECENT FINDING
Publikováno v:
International journal of law and psychiatry. 80
Introduction In 1992, New Zealand's mental health legislation created the distinct concept of a ‘restricted patient’ – effectively creating a pathway into forensic patient status, but via the civil committal process, without the patient passing
Publikováno v:
AIES
There is growing awareness that AI and machine learning systems can in some cases learn to behave in unfair and discriminatory ways with harmful consequences. However, despite an enormous amount of research, techniques for ensuring AI fairness have y
Publikováno v:
WWW
A growing proportion of human interactions are digitized on social media platforms and subjected to algorithmic decision-making, and it has become increasingly important to ensure fair treatment from these algorithms. In this work, we investigate gen