Results 51 to 60 of about 43,983 (273)

Personalized Federated Learning via Variational Bayesian Inference

open access: yesCoRR, 2022
accepted for publication in 39th International Conference on Machine Learning (ICML ...
Xu Zhang 0011   +4 more
openaire   +3 more sources

Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer

open access: yesAging and Cancer, EarlyView.
Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss   +12 more
wiley   +1 more source

Objective Bayesian Inference in Probit Models with Intrinsic Priors Using Variational Approximations

open access: yesEntropy, 2020
There is not much literature on objective Bayesian analysis for binary classification problems, especially for intrinsic prior related methods. On the other hand, variational inference methods have been employed to solve classification problems using ...
Ang Li, Luis Pericchi, Kun Wang
doaj   +1 more source

Sparse Stochastic Inference for Latent Dirichlet allocation

open access: yes, 2012
We present a hybrid algorithm for Bayesian topic models that combines the efficiency of sparse Gibbs sampling with the scalability of online stochastic inference.
Blei, David, Hoffman, Matt, Mimno, David
core   +2 more sources

Streaming, Distributed Variational Inference for Bayesian Nonparametrics

open access: yesCoRR, 2015
This paper presents a methodology for creating streaming, distributed inference algorithms for Bayesian nonparametric (BNP) models. In the proposed framework, processing nodes receive a sequence of data minibatches, compute a variational posterior for each, and make asynchronous streaming updates to a central model.
Campbell, Trevor David   +3 more
openaire   +3 more sources

Shared Genetic Effects and Antagonistic Pleiotropy Between Multiple Sclerosis and Common Cancers

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epidemiologic studies have reported inconsistent altered cancer risk in individuals with multiple sclerosis (MS). Factors such as immune dysregulation, comorbidities, and disease‐modifying therapies may contribute to this variability.
Asli Buyukkurt   +5 more
wiley   +1 more source

Parameter estimation for allometric trophic network models: A variational Bayesian inverse problem approach

open access: yesMethods in Ecology and Evolution
Differential equation models are powerful tools for predicting biological systems, capable of projecting far into the future and incorporating data recorded at arbitrary times.
Maria Tirronen, Anna Kuparinen
doaj   +1 more source

Bayesian compositional regression with microbiome features via variational inference

open access: yesBMC Bioinformatics, 2023
The microbiome plays a key role in the health of the human body. Interest often lies in finding features of the microbiome, alongside other covariates, which are associated with a phenotype of interest. One important property of microbiome data, which is
Darren A. V. Scott   +10 more
doaj   +1 more source

Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling [PDF]

open access: yes, 2016
We study parameter inference in large-scale latent variable models. We first propose an unified treatment of online inference for latent variable models from a non-canonical exponential family, and draw explicit links between several previously proposed ...
Bach, Francis, Dupuy, Christophe
core   +3 more sources

Stochastic variational inference for large-scale discrete choice models using adaptive batch sizes

open access: yes, 2015
Discrete choice models describe the choices made by decision makers among alternatives and play an important role in transportation planning, marketing research and other applications. The mixed multinomial logit (MMNL) model is a popular discrete choice
Tan, Linda S. L.
core   +1 more source

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