Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension

arXiv:2407.00966 · cs.LG, cs.CC · Submitted 2024-07-01 · Read on arXiv

cs.LG, cs.CC

Submitted: 2024-07-01

Updated: 2026-09-02

Terminology

• Agnostic Learning — 31× in this paper · explained in 1 episode
• Gaussian Surface Area — 18× in this paper
• Statistical Query — 11× in this paper
• Intrinsic Dimension — 10× in this paper · explained in 2 episodes
• Adam — 8× in this paper · explained in 2 episodes
• Polynomial Threshold Function — 5× in this paper
• Annual ACM Symposium on Theory of Computing — 4× in this paper
• Anticoncentration — 4× in this paper · explained in 1 episode
• AI Institute for Foundations of Machine Learning — 3× in this paper
• Annual Symposium on Foundations of Computer Science — 3× in this paper
• Accuracy — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Active Learning — 1× in this paper · explained in 6 episodes
• Chebyshev Polynomials — 1× in this paper · explained in 2 episodes
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Sample Complexity — 1× in this paper · explained in 15 episodes

Sources

• Decision trees are PAC-learnable from most product distributions: a smoothed analysis
• Structure from Local Optima: Learning Subspace Juntas via Higher Order PCA

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