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Found 8 papers, 0 papers with code
A replica analysis of under-bagging
Under-bagging (UB), which combines under sampling and bagging, is a popular ensemble learning method for training classifiers on an imbalanced data.
Asymptotic Dynamics of Alternating Minimization for Non-Convex Optimization
This study investigates the asymptotic dynamics of alternating minimization applied to optimize a bilinear non-convex function with normally distributed covariates.
Compressed Sensing Radar Detectors based on Weighted LASSO
Based on this estimator, we construct a detector, termed the debiased weighted LASSO detector (DWLD), for CS radar systems and prove its advantages.
Average case analysis of Lasso under ultra-sparse conditions
The obtained bound for perfect support recovery is a generalization of that given in previous literature, which only considers the case of Gaussian noise and diverging $d$.
Compressed sensing radar detectors under the row-orthogonal design model: a statistical mechanics perspective
Such detector can analytically provide the threshold according to given false alarm rate, which is not possible with the conventional CS detector, and the detection performance is proved to be better than that of the traditional LASSO detector.
The Role of Pseudo-labels in Self-training Linear Classifiers on High-dimensional Gaussian Mixture Data
When the number of iterations is small, ST improves generalization performance by fitting the model to relatively reliable pseudo-labels and updating the model parameters by a large amount at each iteration.
Semi-analytic approximate stability selection for correlated data in generalized linear models
We consider the variable selection problem of generalized linear models (GLMs).
Replicated Vector Approximate Message Passing For Resampling Problem
Resampling techniques are widely used in statistical inference and ensemble learning, in which estimators' statistical properties are essential.
