Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Sinead A. Williamson"'
Autor:
Sinead A. Williamson, Jette Henderson
Publikováno v:
Information, Vol 12, Iss 10, p 392 (2021)
Understanding how two datasets differ can help us determine whether one dataset under-represents certain sub-populations, and provides insights into how well models will generalize across datasets. Representative points selected by a maximum mean dis
Externí odkaz:
https://doaj.org/article/22a41769f4ae460ab7b34eb1a851190f
Publikováno v:
IEEE Transactions on Signal Processing. 71:1539-1550
Many machine learning problems can be framed in the context of estimating functions, and often these are time-dependent functions that are estimated in real-time as observations arrive. Gaussian processes (GPs) are an attractive choice for modeling r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09be6d4137e8bdccf305c58ef5615d7f
https://doi.org/10.1109/tsp.2023.3267992
https://doi.org/10.1109/tsp.2023.3267992
Publikováno v:
Statistics and Computing. 32
Inference of latent feature models in the Bayesian nonparametric setting is generally difficult, especially in high dimensional settings, because it usually requires proposing features from some prior distribution. In special cases, where the integra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::84568a53b148e5291c1b36551af1dfaf
https://doi.org/10.1007/s11222-022-10108-z
https://doi.org/10.1007/s11222-022-10108-z
Publikováno v:
International journal of obesity (2005)
BACKGROUND/OBJECTIVES: Little is currently known about how exercise may influence dietary patterns and/or food preferences. The present study aimed to examine the effect of a 15-week exercise training program on overall dietary patterns among young a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2f9a6d422d7dd8f0a631e1332961acf
https://doi.org/10.1038/s41366-018-0299-3
https://doi.org/10.1038/s41366-018-0299-3
Autor:
Sinead A. Williamson, Steve Draper, Christine Draper, Binnu Jesudasan, Luis Aguirre, Matt Sanchez, Shubham Sharma, Susan Michalski, Yessel Hinojosa, Shahzad Alam, Akarsh Prasad, Michael Criscolo, Valeri Alexiev, Prajna Kandarpa, Colton Lee, Mayank Chutani, Aditya Kumar, Alan H. Gee, Carlos Marin, Shorya Consul, Jette Henderson, Michael Perng, Michael Li, Joydeep Ghosh, Sara Rouhani
Publikováno v:
IJCAI
As more companies and governments build and use machine learning models to automate decisions, there is an ever-growing need to monitor and evaluate these models' behavior once they are deployed. Our team at CognitiveScale has developed a toolkit cal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b4cb131583002572da1050adf0ee173
https://doi.org/10.24963/ijcai.2020/759
https://doi.org/10.24963/ijcai.2020/759
Autor:
Jette Henderson, Sinead A. Williamson
Publikováno v:
Information
Volume 12
Issue 10
Information, Vol 12, Iss 392, p 392 (2021)
Volume 12
Issue 10
Information, Vol 12, Iss 392, p 392 (2021)
Understanding how two datasets differ can help us determine whether one dataset under-represents certain sub-populations, and provides insights into how well models will generalize across datasets. Representative points selected by a maximum mean dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e534e7ad78c4d772566da31be9df4f8
Autor:
Sinead A. Williamson, Maurice Diesendruck, Guy W. Cole, Sanjay Shakkottai, Rajat Sen, Ethan R. Elenberg
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030461461
ECML/PKDD (2)
ECML/PKDD (2)
While deep generative networks can simulate from complex data distributions, their utility can be hindered by limitations on the data available for training. Specifically, the training data distribution may differ from the target sampling distributio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0089eb92ba77a82c7acb043cb1a9abb
https://doi.org/10.1007/978-3-030-46147-8_15
https://doi.org/10.1007/978-3-030-46147-8_15
Publikováno v:
DAC
As integrated circuit technologies continue to scale, efficient performance modeling becomes indispensable. Recently, several new learning paradigms have been proposed to reduce the computational cost associated with accurate performance modeling. A
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::582ae9eec00f8839d314e014ec7bf94a
https://doi.org/10.1145/3316781.3317896
https://doi.org/10.1145/3316781.3317896
BACKGROUND: Principal components analysis (PCA) has been the most widely used method for deriving dietary patterns to date. However, PCA requires arbitrary ad hoc decisions for selecting food variables in interpreting dietary patterns and does not ea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6443ef9cb37978128be3cee96daa749e
https://europepmc.org/articles/PMC6280002/
https://europepmc.org/articles/PMC6280002/
Publikováno v:
J Comput Graph Stat
We develop a scalable multi-step Monte Carlo algorithm for inference under a large class of nonparametric Bayesian models for clustering and classification. Each step is "embarrassingly parallel" and can be implemented using the same Markov chain Mon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e17b1c66ca1ff91e4aaa35af26cf03b3