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Neural lasso: a unifying approach of lasso and neural networks
In recent years, there has been a growing interest in establishing bridges between statistics and neural networks. This article focuses on the...
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Unlocking the Lookup Singularity with Lasso
This paper introduces Lasso, a new family of lookup arguments, which allow an untrusted prover to commit to a vector...
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Kleene Theorems for Lasso Languages and \(\omega \) -Languages
Automata operating on pairs of words were introduced as an alternative way of capturing acceptance of regular...
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Lasso and Friends
Regularized linear models are generalized linear regression models with a penalty for large coefficients to regulate the bias-variance tradeoff. For...
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Variable screening for Lasso based on multidimensional indexing
In this paper we present a correlation based safe screening technique for building the complete Lasso path. Unlike many other Lasso screening...
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Lasso-Cox interpretable model of AFP-negative hepatocellular carcinoma
BackgroundIn AFP-negative hepatocellular carcinoma patients, markers for predicting tumor progression or prognosis are limited. Therefore, our...
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Group LASSO for Change-points in Functional Time Series
Multiple change-points estimation for functional time series is studied in this paper. The change-point problem is first transformed into a...
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Bayesian fused lasso modeling via horseshoe prior
Bayesian fused lasso is one of the sparse Bayesian methods, which shrinks both regression coefficients and their successive differences...
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Fused lasso nearly-isotonic signal approximation in general dimensions
In this paper, we introduce and study fused lasso nearly-isotonic signal approximation, which is a combination of fused lasso and generalized...
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Application and impact of Lasso regression in gastroenterology: A systematic review
Least absolute shrinkage and selection operator (Lasso) regression is a statistical technique that can be used to study the effects of clinical...
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Lasso and Ridge for GARCH-X Models
This paper examines the efficacy of the least absolute shrinkage and selection operator (Lasso) and Ridge algorithms in improving the volatility...
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Automatic grid topology detection method based on Lasso algorithm and t-SNE algorithm
For a long time, the low-voltage distribution network has the problems of untimely management and complex and frequently changing lines, which makes...
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Lasso Selection Tools
This chapter shows how to use the Lasso, Polygonal, and Magnetic Lasso tools to get a more accurate selection of the area depending on the...
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Hierarchical Bayesian adaptive lasso methods on exponential random graph models
The analysis of network data has become an increasingly prominent and demanding field across multiple research fields including data science, health,...
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Robustness of Graphical Lasso Optimization Algorithm for Learning a Graphical Model
Problem of learning a graphical model (graphical model selection problem) consists of recovering a conditional dependence structure (concentration...
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Combining LASSO-type Methods with a Smooth Transition Random Forest
In this work, we propose a novel hybrid method for the estimation of regression models, which is based on a combination of LASSO-type methods and...
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Variational Bayesian Lasso for spline regression
This work presents a new scalable automatic Bayesian Lasso methodology with variational inference for non-parametric splines regression that can...
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Combining Feature Selection and Classification Using LASSO-Based MCO Classifier for Credit Risk Evaluation
Credit risk evaluation is a difficult task to predict default probabilities and deduce risk classification, and many classification methods and...
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Meta-lasso: new insight on infection prediction after minimally invasive surgery
AbstractSurgical site infection (SSI) after minimally invasive lung cancer surgery constitutes an important factor influencing the direct and...
