arXiv Statistics ML
Scale-invariant Optimal Sampling for Rare-events Data with Sparse Models
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A Nonconvex Framework for Joint Sparse Sample Weighting and Parameter Estimation
arXiv:2610.33957v1 Announce Type: cross Abstract: We propose a joint sparse sample weighting and parameter estimation (SWAPE) framework that jointly optimizes model parameters and sample weights to t...
arXiv Machine Learning
Jul 10
The Regularization Parameter: Sparse Precision Matrix Estimation
arXiv:2607. 07735v1 Announce Type: cross Abstract: Sparse precision matrix estimation provides an interpretable and computationally efficient framework for modeling conditional dependencies in high-dimensional, low-sample-size data.
arXiv AI
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When Data Is Scarce: Scaling Sparse Language Models with Repeated Training
arXiv:2606. 01155v1 Announce Type: cross Abstract: Scaling laws for dense LLMs under infinite data are well explored, but how sparsity interacts with limited data is not.
arXiv Machine Learning
Jun 11
Renewable Lasso without Batch-Number Constraints: A Gradient-Enhanced Approach
arXiv:2606. 11738v1 Announce Type: cross Abstract: We study online estimation for high-dimensional generalized linear models with streaming data.
arXiv Machine Learning
Oct 7
High-Dimensional Statistical Inference for Sparse Support Vector Machines
arXiv:2610.08345v1 Announce Type: cross Abstract: Using a replica-symmetric high-dimensional characterization, we develop an inferential framework for sparse support vector machines when the sample s...
arXiv Machine Learning
Sep 30
LOCO-AdaMP: Built-in LOCO Inference for Adaptive Minipatch Ensembles with Enhanced Prediction
arXiv:2609.36396v1 Announce Type: cross Abstract: As black-box machine learning models become increasingly common, extracting interpretations with uncertainty quantification has become a critical cha...