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Gaussian process with derivative information for the analysis of the sunlight ad ...
Microfading Spectrometry (MFS) is a method for assessing light sensitivity color (spectral) variations of cultural heritage objects. The MFS technique provides measurements of the surface under study, where each point of the sur ... Read More >
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Confidence Intervals for Policy Evaluation in Adaptive Experiments
Adaptive experiment designs can dramatically improve statistical efficiency in randomized trials, but they also complicate statistical inference. For example, it is now well known that the sample mean is biased in adaptive trial ... Read More >
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An Efficient Algorithm for Capacity-Approaching Noisy Adaptive Group Testing
In this paper, we consider the group testing problem with adaptive test designs and noisy outcomes. We propose a computationally efficient four-stage procedure with components including random binning, identification of bins con ... Read More >
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Optimal Projections in the Distance-Based Statistical Methods
This paper introduces a new way to calculate distance-based statistics, particularly when the data are multivariate. The main idea is to pre-calculate the optimal projection directions given the variable dimension, and to projec ... Read More >
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Data transforming augmentation for heteroscedastic models
Data augmentation (DA) turns seemingly intractable computational problems into simple ones by augmenting latent missing data. In addition to computational simplicity, it is now well-established that DA equipped with a determinis ... Read More >
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Valid Two-Sample Graph Testing via Optimal Transport Procrustes and Multiscale G ...
Testing whether two graphs come from the same distribution is of interest in many real world scenarios, including brain network analysis. Under the random dot product graph model, the nonparametric hypothesis testing frame-work ... Read More >
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Statistical Analysis of Dynamic Functional Brain Networks in Twins
Recent studies have shown that functional brain brainwork is dynamic even during rest. A common approach to modeling the brain network in whole brain resting-state fMRI is to compute the correlation between anatomical regions vi ... Read More >
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Auto-encoding brain networks with applications to analyzing large-scale brain im ...
There has been huge interest in studying human brain connectomes inferred from different imaging modalities and exploring their relationship with human traits, such as cognition. Brain connectomes are usually represented as netw ... Read More >
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Scalable Algorithms for Large Competing Risks Data
This paper develops two orthogonal contributions to scalable sparse regression for competing risks time-to-event data. First, we study and accelerate the broken adaptive ridge method (BAR), an $\ell_0$-based iteratively reweight ... Read More >
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Invariance and identifiability issues for word embeddings
Word embeddings are commonly obtained as optimizers of a criterion function $f$ of a text corpus, but assessed on word-task performance using a different evaluation function $g$ of the test data. We contend that a possible sourc ... Read More >