Show newer

Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. (arXiv:2202.05928v1 [cs.LG]) arxiv.org/abs/2202.05928

POT-flavored estimator of Pickands dependence function. (arXiv:2202.05935v1 [stat.ME]) arxiv.org/abs/2202.05935

Private Adaptive Optimization with Side Information. (arXiv:2202.05963v1 [cs.LG]) arxiv.org/abs/2202.05963

scpi: Uncertainty Quantification for Synthetic Control Estimators. (arXiv:2202.05984v1 [stat.ME]) arxiv.org/abs/2202.05984

Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning. (arXiv:2202.06052v1 [cs.LG]) arxiv.org/abs/2202.06052

Relaxing the Feature Covariance Assumption: Time-Variant Bounds for Benign Overfitting in Linear Regression. (arXiv:2202.06054v1 [cs.LG]) arxiv.org/abs/2202.06054

Depth profiles and the geometric exploration of random objects through optimal transport. (arXiv:2202.06117v1 [stat.ME]) arxiv.org/abs/2202.06117

A Field of Experts Prior for Adapting Neural Networks at Test Time. (arXiv:2202.05271v1 [cs.CV]) arxiv.org/abs/2202.05271

Universal Learning Waveform Selection Strategies for Adaptive Target Tracking. (arXiv:2202.05294v1 [cs.IT]) arxiv.org/abs/2202.05294

Personalization Improves Privacy-Accuracy Tradeoffs in Federated Optimization. (arXiv:2202.05318v1 [stat.ML]) arxiv.org/abs/2202.05318

Robust Parameter Estimation for the Lee-Carter Model: A Probabilistic Principal Component Approach. (arXiv:2202.05349v1 [stat.ME]) arxiv.org/abs/2202.05349

Network Interference in Micro-Randomized Trials. (arXiv:2202.05356v1 [stat.ME]) arxiv.org/abs/2202.05356

Bayesian learning of COVID-19 Vaccine safety while incorporating Adverse Events ontology. (arXiv:2202.05370v1 [stat.ME]) arxiv.org/abs/2202.05370

Investigating cognitive ability using action-based models of structural brain networks. (arXiv:2202.05389v1 [q-bio.NC]) arxiv.org/abs/2202.05389

Multivariate distance matrix regression for a manifold-valued response variable. (arXiv:2202.05401v1 [stat.ME]) arxiv.org/abs/2202.05401

High-dimensional properties for empirical priors in linear regression with unknown error variance. (arXiv:2202.05419v1 [math.ST]) arxiv.org/abs/2202.05419

A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability. (arXiv:2202.05420v1 [cs.LG]) arxiv.org/abs/2202.05420

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems. (arXiv:2202.04648v1 [cs.LG]) arxiv.org/abs/2202.04648

Bayesian Nonparametrics for Offline Skill Discovery. (arXiv:2202.04675v1 [cs.LG]) arxiv.org/abs/2202.04675

Smoothed Online Learning is as Easy as Statistical Learning. (arXiv:2202.04690v1 [stat.ML]) arxiv.org/abs/2202.04690

Show older
Qoto Mastodon

QOTO: Question Others to Teach Ourselves
An inclusive, Academic Freedom, instance
All cultures welcome.
Hate speech and harassment strictly forbidden.