Stochastic tensor space feature theory with applications to robust machine learning

arXiv:2110.01729 · stat.ML, cs.LG · Submitted 2021-10-04 · Read on arXiv

stat.ML, cs.LG

Submitted: 2021-10-04

Updated: 2026-09-16

Code: https://github.com/jcandas/Finder-StochasticTensor

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 59× in this paper · explained in 1 episode
• Machine Learning — 20× in this paper
• AUC — 14× in this paper · explained in 2 episodes
• Support Vector Machine — 9× in this paper
• Cognitive Normal — 4× in this paper
• Functional Data Analysis — 4× in this paper
• Mild Cognitive Impairment — 4× in this paper
• Multilevel Orthogonal Subspace — 3× in this paper
• Hilbert Space — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Late Mild Cognitive Impairment — 1× in this paper
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Principal Component Analysis — 1× in this paper
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Receiver Operating Characteristic — 1× in this paper
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• Distribution-Free Stochastic Analysis and Robust Multilevel Vector Field Anomaly Detection

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