Sparse Regression Distilled from a Single Robust Fit

arXiv:2609.23937 · stat.ML, cs.LG, stat.ME · Submitted 2026-09-20 · Read on arXiv

stat.ML, cs.LG, stat.ME

Submitted: 2026-09-20

Updated: 2026-09-20

Comments: 68 pages, including appendices; 8 figures

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

Terminology

Distillation — 47× in this paper · explained in 2 episodes
Fidelity — 43× in this paper · explained in 2 episodes
Robustness — 19× in this paper · explained in 5 episodes
Accuracy — 12× in this paper · explained in 1 episode
Consistency — 9× in this paper · explained in 3 episodes
Benchmark — 8× in this paper · explained in 2 episodes
Parsimony — 8× in this paper · explained in 2 episodes
Provenance — 8× in this paper · explained in 3 episodes
Core — 6× in this paper · explained in 2 episodes
Feature Selection — 3× in this paper · explained in 4 episodes
Heteroscedasticity — 3× in this paper · explained in 2 episodes
Sparsity — 3× in this paper · explained in 4 episodes
Degeneracy — 2× in this paper · explained in 3 episodes
Regularization — 2× in this paper · explained in 3 episodes
Trace — 2× in this paper · explained in 2 episodes
Abstraction — 1× in this paper · explained in 1 episode
Calibration — 1× in this paper · explained in 7 episodes
Decoupling — 1× in this paper · explained in 2 episodes
Explainability — 1× in this paper · explained in 3 episodes
Influence Functions — 1× in this paper · explained in 2 episodes
Interpretability — 1× in this paper · explained in 15 episodes
Modularity — 1× in this paper · explained in 9 episodes
National Research Foundation of Korea — 1× in this paper
Pairwise Comparisons — 1× in this paper · explained in 2 episodes

Sources

Distilling the Knowledge in a Neural Network

Related papers