Mixed effects neural networks (menets) with applications to gaze estimation
There is much interest in computer vision to utilize commodity hardware for gaze estimation.
A number of papers have shown that algorithms based on deep convolutional architectures …
A number of papers have shown that algorithms based on deep convolutional architectures …
To split or not to split: The impact of disparate treatment in classification
Disparate treatment occurs when a machine learning model produces different decisions for
individuals based on a legally protected or sensitive attribute (eg, age, sex). In domains …
individuals based on a legally protected or sensitive attribute (eg, age, sex). In domains …
Sparse group lasso: Optimal sample complexity, convergence rate, and statistical inference
We study sparse group Lasso for high-dimensional double sparse linear regression, where
the parameter of interest is simultaneously element-wise and group-wise sparse. This …
the parameter of interest is simultaneously element-wise and group-wise sparse. This …
Merging versus ensembling in multi-study prediction: theoretical insight from random effects
A critical decision point when training predictors using multiple studies is whether these
studies should be combined or treated separately. We compare two multi-study learning …
studies should be combined or treated separately. We compare two multi-study learning …
Double burden of malnutrition among women and children in Zimbabwe: a pooled logistic regression and Oaxaca-Blinder decomposition analysis
Background The double burden of malnutrition (DBM) is a public health issue characterised
by the coexistence of undernutrition and overnutrition within the same population …
by the coexistence of undernutrition and overnutrition within the same population …
Equivariance allows handling multiple nuisance variables when analyzing pooled neuroimaging datasets
VS Lokhande, R Chakraborty… - Proceedings of the …, 2022 - openaccess.thecvf.com
Pooling multiple neuroimaging datasets across institutions often enables significant
improvements in statistical power when evaluating associations (eg, between risk factors …
improvements in statistical power when evaluating associations (eg, between risk factors …
Pooling Image Datasets With Multiple Covariate Shift and Imbalance
Small sample sizes are common in many disciplines, which necessitates pooling roughly
similar datasets across multiple institutions to study weak but relevant associations between …
similar datasets across multiple institutions to study weak but relevant associations between …
The impact of split classifiers on group fairness
Disparate treatment occurs when a machine learning model produces different decisions for
groups of individuals based on a sensitive attribute (eg, age, sex). In domains where …
groups of individuals based on a sensitive attribute (eg, age, sex). In domains where …
College Students and “Interracial” Relationships: How Our Measures Matter
KH Tillman, L Ramirez Surmeier, B Miller - Social Currents, 2023 - journals.sagepub.com
We use data from a random sample of students collected at two large public universities,
one in the Midwestern region and one in the Southeastern region of the US, to document the …
one in the Midwestern region and one in the Southeastern region of the US, to document the …
[图书][B] High-Dimensional Inference for Low-Dimensional Structures: Double Sparse Vectors and Low-Rank Tensors
Y Zhou - 2021 - search.proquest.com
High-dimensional statistics has attracted considerable attention in recent years. To achieve
reliable estimation and uncertainty quantification, some low-dimensional structures …
reliable estimation and uncertainty quantification, some low-dimensional structures …