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A Model of Double Descent for High-dimensional Binary Linear Classification
We consider a model for logistic regression where only a subset of features of size $p$ is used for training a linear classifier over $n$ training samples. The classifier is obtained by running gradient descent (GD) on logistic ... Read More >
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A Simulation-free Group Sequential Design with Max-combo Tests in the Presence o ...
Non-proportional hazards (NPH) have been observed recently in many immuno-oncology clinical trials. Weighted log-rank tests (WLRT) with suitably chosen weights can be used to improve the power of detecting the difference of the ... Read More >
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Exponential Convergence Rates of Classification Errors on Learning with SGD and ...
Although kernel methods are widely used in many learning problems, they have poor scalability to large datasets. To address this problem, sketching and stochastic gradient methods are the most commonly used techniques to derive ... Read More >
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Identifying predictive biomarkers of CIMAvaxEGF success in advanced Lung Cancer ...
Objectives: To identify predictive biomarkers of CIMAvaxEGF success in the treatment of Non-Small Cell Lung Cancer Patients. Methods: Data from a clinical trial evaluating the effect on survival time of CIMAvax-EGF versus best s ... Read More >
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Causality-based tests to detect the influence of confounders on mobile health di ...
Machine learning practice is often impacted by confounders. Confounding can be particularly severe in remote digital health studies where the participants self-select to enter the study. While many different confounding adjustme ... Read More >
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Robust Fitting for Generalized Additive Models for Location, Scale and Shape
The validity of estimation and smoothing parameter selection for the wide class of generalized additive models for location, scale and shape (GAMLSS) relies on the correct specification of a likelihood function. Deviations from ... Read More >
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Harmonic Mean Point Processes: Proportional Rate Error Minimization for Obtundat ...
In healthcare, the highest risk individuals for morbidity and mortality are rarely those with the greatest modifiable risk. By contrast, many machine learning formulations implicitly attend to the highest risk individuals. We fo ... Read More >
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The effect of geographic sampling on evaluation of extreme precipitation in high ...
Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station data. For modern high-resolution models, this is ... Read More >
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Purifying Interaction Effects with the Functional ANOVA: An Efficient Algorithm ...
Models which estimate main effects of individual variables alongside interaction effects have an identifiability challenge: effects can be freely moved between main effects and interaction effects without changing the model pred ... Read More >
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Intraday Retail Sales Forecast: An Efficient Algorithm for Quantile Additive Mod ...
With the ever increasing prominence of data in retail operations, sales forecasting has become an essential pillar in the efficient management of inventories. When facing high demand, the use of backroom storage and intraday she ... Read More >