Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sinead Williamson"'
Machine learning methods allow us to make recommendations to users in applications across fields including entertainment, dating, and commerce, by exploiting similarities in users' interaction patterns. However, in domains that demand protection of p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68f16fa72302021d64229b0052291031
Hierarchical clustering methods offer an intuitive and powerful way to model a wide variety of data sets. However, the assumption of a fixed hierarchy is often overly restrictive when working with data generated over a period of time: We expect both
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6440ec3c50d8befe40a81a4d4bc6a94b
The Pitman-Yor process provides an elegant way to cluster data that exhibit power law behavior, where the number of clusters is unknown or unbounded. Unfortunately, inference in PitmanYor process-based models is typically slow and does not scale well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::457d4248b5af38931458fc80b9af0154
Distributions over exchangeable matrices with infinitely many columns are useful in constructing nonparametric latent variable models. However, the distribution implied by such models over the number of features exhibited by each data point may be po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::42956b5f7d2fc1c0598e2bb1fcfb4853
Nonparametric mixture models based on the Dirichlet process are an elegant alternative to finite models when the number of underlying components is unknown, but inference in such models can be slow. Existing attempts to parallelize inference in such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::388606162eac68f9397e1a7609c36784