Machine Learning Integrated in Wavelet Shrinkage (MLShrink)

arXiv:2606.19580 · stat.ME, stat.ML · Submitted 2026-06-17 · Read on arXiv

Dixon Vimalajeewa, Vijini Lakmini, Brani Vidakovic

stat.ME, stat.ML

Submitted: 2026-06-17

Code: https://github.com/Vijini95/MLShrink

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

Terminology

Benchmark — 14× in this paper · explained in 2 episodes
Consistency — 7× in this paper · explained in 3 episodes
Logistic Regression — 4× in this paper
Regularization — 4× in this paper · explained in 3 episodes
Transformer — 4× in this paper · explained in 2 episodes
Wavelet Transform — 3× in this paper · explained in 2 episodes
Class Imbalance — 2× in this paper · explained in 3 episodes
Coherence — 2× in this paper · explained in 2 episodes
Minimax Optimality — 2× in this paper · explained in 3 episodes
Transformers — 2× in this paper · explained in 2 episodes
Accuracy — 1× in this paper · explained in 1 episode
Attention Mechanism — 1× in this paper · explained in 3 episodes
Contrastive Learning — 1× in this paper · explained in 9 episodes
Editor — 1× in this paper · explained in 2 episodes
Feature Engineering — 1× in this paper · explained in 3 episodes
Heteroscedasticity — 1× in this paper · explained in 2 episodes
Interpretability — 1× in this paper · explained in 15 episodes
Iterative Refinement — 1× in this paper · explained in 5 episodes
Localization — 1× in this paper · explained in 2 episodes
Pseudo-labeling — 1× in this paper · explained in 3 episodes
Reconstruction Error — 1× in this paper · explained in 2 episodes
Representation Learning — 1× in this paper · explained in 3 episodes
Structural Properties — 1× in this paper · explained in 2 episodes

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