Adaptive Subspace Modeling With Functional Tucker Decomposition

arXiv:2603.25530 · stat.ML, cs.NA, math.NA · Submitted 2026-03-26 · Read on arXiv

stat.ML, cs.NA, math.NA

Submitted: 2026-03-26

Updated: 2026-09-25

Terminology

• Tucker Decomposition — 44× in this paper · explained in 2 episodes
• Core — 16× in this paper · explained in 2 episodes
• F1 Score — 16× in this paper · explained in 3 episodes
• Accuracy — 10× in this paper · explained in 1 episode
• Hilbert Space — 8× in this paper · explained in 2 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• Adaptability — 3× in this paper · explained in 1 episode
• Data Fusion — 2× in this paper · explained in 3 episodes
• Reproducing Kernel Hilbert Space (RKHS) — 2× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Computational Tractability — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• NYC Taxi and Limousine Commission — 1× in this paper
• Objective Function — 1× in this paper · explained in 2 episodes
• Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes

Related papers

• Behavior of prediction performance metrics with rare events
• Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
• A Posterior-Dynamics Framework for Imaging Inverse Problems with Pretrained Diffusion Priors
• One Permutation Is All You Need: Fast, Deterministic Feature Importance and Model Stress-Testing
• Online Conformal Prediction for Non-Exchangeable Panel Data
• Deep Time-Series Forecasting in 10 Years: A Survey