Terminal Dimension Reduction for Time Series with Applications

arXiv:2607.09490 · cs.DS, cs.CG, cs.LG, stat.ML · Submitted 2026-07-10 · Read on arXiv

Alexander Munteanu, Matteo Russo, David Saulpic, Chris Schwiegelshohn

cs.DS, cs.CG, cs.LG, stat.ML

Submitted: 2026-07-10

Comments: ICML 2026

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

Terminology

Clustering — 82× in this paper · explained in 2 episodes
Embeddings — 73× in this paper · explained in 2 episodes
Editor — 30× in this paper · explained in 2 episodes
Orthogonal Projection — 7× in this paper · explained in 2 episodes
Generalization — 5× in this paper · explained in 14 episodes
Core — 3× in this paper · explained in 2 episodes
VC Dimension — 3× in this paper · explained in 2 episodes
Dimensionality Reduction — 2× in this paper · explained in 2 episodes
Distance Preservation — 2× in this paper · explained in 2 episodes
Loss Function — 2× in this paper · explained in 2 episodes
Parameterization — 2× in this paper · explained in 2 episodes
Sparsity — 2× in this paper · explained in 5 episodes
Accuracy — 1× in this paper · explained in 1 episode
Active Learning — 1× in this paper · explained in 6 episodes
Composition — 1× in this paper · explained in 2 episodes
Generalization Bounds — 1× in this paper · explained in 2 episodes
Monotonicity — 1× in this paper · explained in 2 episodes
Papers — 1× in this paper · explained in 3 episodes
Principal Component Analysis (PCA) — 1× in this paper · explained in 8 episodes
Scale-Invariance — 1× in this paper · explained in 2 episodes
Trace — 1× in this paper · explained in 2 episodes

Sources

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