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Predicting colorectal polyp recurrence using time-to-event analysis of medical r ...
Identifying patient characteristics that influence the rate of colorectal polyp recurrence can provide important insights into which patients are at higher risk for recurrence. We used natural language processing to extract poly ... Read More >
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Stochastic Gradient Annealed Importance Sampling for Efficient Online Marginal L ...
We consider estimating the marginal likelihood in settings with independent and identically distributed (i.i.d.) data. We propose estimating the predictive distributions in a sequential factorization of the marginal likelihood i ... Read More >
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A Permutation Test for Assessing the Presence of Individual Differences in Treat ...
One size fits all approaches to medicine have become a thing of the past as the understanding of individual differences grows. The paper introduces a test for the presence of heterogeneity in treatment effects in a clinical tria ... Read More >
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Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inferen ...
A new algorithm is developed to tackle the issue of sampling non-Gaussian model parameter posterior probability distributions that arise from solutions to Bayesian inverse problems. The algorithm aims to mitigate some of the hur ... Read More >
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Partial Least Squares for Functional Joint Models
Many biomedical studies have identified important imaging biomarkers that are associated with both repeated clinical measures and a survival outcome. The functional joint model (FJM) framework, proposed in Li and Luo (2017), inv ... Read More >
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Defending Against Model Stealing Attacks with Adaptive Misinformation
Deep Neural Networks (DNNs) are susceptible to model stealing attacks, which allows a data-limited adversary with no knowledge of the training dataset to clone the functionality of a target model, just by using black-box query a ... Read More >
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Bayesian Ordinal Quantile Regression with a Partially Collapsed Gibbs Sampler
Unlike standard linear regression, quantile regression captures the relationship between covariates and the conditional response distribution as a whole, rather than only the relationship between covariates and the expected valu ... Read More >
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Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration
The task of inertial sensor calibration has required the development of various techniques to take into account the sources of measurement error coming from such devices. The calibration of the stochastic errors of these sensors ... Read More >
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Marginal and Interactive Feature Screening of Ultra-high Dimensional Feature Spa ...
When the number of features exponentially outnumbers the number of samples, feature screening plays a pivotal role in reducing the dimension of the feature space and developing models based on such data. While most extant featur ... Read More >
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Scalable and Accurate Variational Bayes for High-Dimensional Binary Regression M ...
Modern methods for Bayesian regression beyond the Gaussian response setting are often computationally impractical or inaccurate in high dimensions. In fact, as discussed in recent literature, bypassing such a trade-off is still ... Read More >