Scalable Minimum-Volume Simplex Estimation with Non-asymptotic Analysis

arXiv:2609.25576 · stat.ML, cs.LG · Submitted 2026-09-22 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-22

Updated: 2026-09-25

Code: https://github.com/ASDFFGG121EAA/DeepMVSA

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

Terminology

Abundance — 37× in this paper · explained in 1 episode
Accuracy — 28× in this paper · explained in 1 episode
Benchmark — 26× in this paper · explained in 2 episodes
Adam — 13× in this paper · explained in 2 episodes
Sample Complexity — 9× in this paper · explained in 15 episodes
Calibration — 7× in this paper · explained in 7 episodes
Regularization — 4× in this paper · explained in 3 episodes
Non-asymptotic Analysis — 3× in this paper · explained in 2 episodes
Ambient Dimension — 2× in this paper · explained in 1 episode
Computational Biology — 2× in this paper · explained in 2 episodes
Consistency — 2× in this paper · explained in 3 episodes
Core — 2× in this paper · explained in 2 episodes
Activation Function — 1× in this paper · explained in 1 episode
Degeneracy — 1× in this paper · explained in 3 episodes
Fidelity — 1× in this paper · explained in 2 episodes
Normalizing Flow — 1× in this paper · explained in 3 episodes
Normalizing Flows — 1× in this paper · explained in 4 episodes
Reconstruction Error — 1× in this paper · explained in 2 episodes
Robustness — 1× in this paper · explained in 5 episodes
Scaling Laws — 1× in this paper · explained in 4 episodes
Theoretical Guarantees — 1× in this paper · explained in 2 episodes
Transformer — 1× in this paper · explained in 2 episodes
Two-stage training — 1× in this paper · explained in 2 episodes

Sources

Fundamental Limits of Learning High-dimensional Simplices in Noisy Regimes

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