Exponential-Family Tensor Completion via Nonconvex Dual Total-Variation Regularization

arXiv:2606.30958 · stat.ME, math.OC, math.ST, stat.ML · Submitted 2026-06-29 · Read on arXiv

Wenfei Cao, Yang Chen, Qibin Zhao, Jinglai Li, Andrzej Cichocki

stat.ME, math.OC, math.ST, stat.ML

Submitted: 2026-06-29

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

Terminology

• Regularization — 56× in this paper · explained in 3 episodes
• Sparsity — 19× in this paper · explained in 5 episodes
• Total Variation — 18× in this paper
• Nuclear Norm — 17× in this paper · explained in 2 episodes
• Matrix Completion — 9× in this paper · explained in 4 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Generalization — 4× in this paper · explained in 14 episodes
• Inverse Problem — 3× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Papers — 2× in this paper · explained in 3 episodes
• Signal-to-Noise Ratio — 2× in this paper
• Alternating Direction Method of Multipliers (ADMM) — 1× in this paper · explained in 2 episodes
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Fusion — 1× in this paper · explained in 3 episodes
• Dimensionality Reduction — 1× in this paper · explained in 2 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Editor — 1× in this paper · explained in 2 episodes
• Fast Fourier Transform — 1× in this paper
• Geometric Distribution — 1× in this paper · explained in 2 episodes
• Mean Peak Signal-to-Noise Ratio — 1× in this paper
• Mean Square Error — 1× in this paper
• Objective Function — 1× in this paper · explained in 2 episodes
• Orthogonal Projection — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 6 episodes
• Signal-to-Noise Ratio (SNR) — 1× in this paper · explained in 6 episodes
• Tucker Decomposition — 1× in this paper · explained in 2 episodes

Sources

• Approximation Theory of Total Variation Minimization for Data Completion
• One-Bit Total Variation Denoising over Networks with Applications to Partially Observed Epidemics

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