Transfer Learning in High-dimensional Ising Models

arXiv:2607.03005 · cs.LG, stat.ME, stat.ML · Submitted 2026-07-03 · Read on arXiv

Joonho Kim, Seyoung Park

cs.LG, stat.ME, stat.ML

Submitted: 2026-07-03

Comments: Published as a conference paper at ICML 2026

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

Terminology

• Transfer Learning — 64× in this paper · explained in 16 episodes
• Lasso — 22× in this paper · explained in 2 episodes
• Consistency — 15× in this paper · explained in 3 episodes
• Sparsity — 10× in this paper · explained in 5 episodes
• Regularization — 6× in this paper · explained in 3 episodes
• Calibration — 4× in this paper · explained in 9 episodes
• Variance Reduction — 4× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Heterogeneous Graph — 2× in this paper · explained in 2 episodes
• Overfitting — 2× in this paper · explained in 2 episodes
• Transferability — 2× in this paper · explained in 5 episodes
• Verification — 2× in this paper · explained in 2 episodes
• AUC — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 12 episodes
• Error Decomposition — 1× in this paper · explained in 4 episodes
• False Negatives — 1× in this paper · explained in 2 episodes
• Fisher Information — 1× in this paper · explained in 4 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Local Optimization — 1× in this paper · explained in 2 episodes
• Localization — 1× in this paper · explained in 2 episodes
• Meta-learning — 1× in this paper · explained in 3 episodes
• Minimax Optimality — 1× in this paper · explained in 3 episodes
• Papers — 1× in this paper · explained in 3 episodes
• Phase Transition — 1× in this paper · explained in 3 episodes
• Polarization — 1× in this paper · explained in 2 episodes
• Receiver Operating Characteristic — 1× in this paper
• Smoothly Clipped Absolute Deviation — 1× in this paper
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 6 episodes

Sources

• Transfer Learning for Nonparametric Regression: Non-asymptotic Minimax Analysis and Adaptive Procedure

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