arXiv Statistics @arxiv_stats@social.cleverlibre.org

On Statistical Bias In Active Learning: How and When To Fix It. (arXiv:2101.11665v1 [stat.ML]) http://arxiv.org/abs/2101.11665

The AL-Gaussian Distribution as the Descriptive Model for the Internal Proactive Inhibition in the Standard Stop Signal Task. (arXiv:2101.11682v1 [stat.ME]) http://arxiv.org/abs/2101.11682

Hadamard Powers and the Identification of Mixtures of Products. (arXiv:2101.11688v1 [cs.LG]) http://arxiv.org/abs/2101.11688

Overestimation learning with guarantees. (arXiv:2101.11717v1 [cs.LG]) http://arxiv.org/abs/2101.11717

Convergence Analysis of Fixed Point Chance Constrained Optimal Power Flow Problems. (arXiv:2101.11740v1 [math.OC]) http://arxiv.org/abs/2101.11740

Learning $\mathbf{\mathit{Matching}}$ Representations for Individualized Organ Transplantation Allocation. (arXiv:2101.11769v1 [stat.ML]) http://arxiv.org/abs/2101.11769

Random Graph Matching with Improved Noise Robustness. (arXiv:2101.11783v1 [cs.DS]) http://arxiv.org/abs/2101.11783

A Kernel-Based Neural Network for High-dimensional Genetic Risk Prediction Analysis. (arXiv:2101.11807v1 [stat.ME]) http://arxiv.org/abs/2101.11807

Interpolating Classifiers Make Few Mistakes. (arXiv:2101.11815v1 [stat.ML]) http://arxiv.org/abs/2101.11815

Inference of stochastic time series with missing data. (arXiv:2101.11816v1 [physics.data-an]) http://arxiv.org/abs/2101.11816

FDApy: a Python package for functional data. (arXiv:2101.11003v1 [cs.MS]) http://arxiv.org/abs/2101.11003

Quantum machine learning models are kernel methods. (arXiv:2101.11020v1 [quant-ph]) http://arxiv.org/abs/2101.11020

Average Localised Proximity: a new data descriptor with good default one-class classification performance. (arXiv:2101.11037v1 [cs.LG]) http://arxiv.org/abs/2101.11037

Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems. (arXiv:2101.11041v1 [math.OC]) http://arxiv.org/abs/2101.11041

Generalized Doubly Reparameterized Gradient Estimators. (arXiv:2101.11046v1 [stat.ML]) http://arxiv.org/abs/2101.11046

Large-scale Optimization with Linear Equality Constraints using Reduced Compact Representation. (arXiv:2101.11048v1 [math.OC]) http://arxiv.org/abs/2101.11048

LDLE: Low Distortion Local Eigenmaps. (arXiv:2101.11055v1 [math.SP]) http://arxiv.org/abs/2101.11055

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. (arXiv:2101.11071v1 [cs.LG]) http://arxiv.org/abs/2101.11071

Tree boosting for learning probability measures. (arXiv:2101.11083v1 [stat.ME]) http://arxiv.org/abs/2101.11083

A general method for power analysis in testing high dimensional covariance matrices. (arXiv:2101.11086v1 [math.ST]) http://arxiv.org/abs/2101.11086