Sample-Efficient Optimization over Generative Priors via Coarse Learnability

arXiv:2503.06917 · cs.LG, cs.DS, stat.ML · Submitted 2025-03-10 · Read on arXiv

cs.LG, cs.DS, stat.ML

Submitted: 2025-03-10

Updated: 2026-10-08

Terminology

• Generative Model — 32× in this paper · explained in 2 episodes
• Sample Complexity — 31× in this paper · explained in 15 episodes
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Generative Models — 10× in this paper · explained in 3 episodes
• Model-Based Optimization — 10× in this paper
• Model Reference Adaptive Search — 8× in this paper
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Adam — 5× in this paper · explained in 2 episodes
• Combinatorial Optimization — 3× in this paper · explained in 2 episodes
• Kernel Density Estimation — 3× in this paper
• Transformer — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Bayesian Inference — 2× in this paper · explained in 5 episodes
• Bayesian Optimization — 2× in this paper · explained in 3 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Regret — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• VC Dimension — 2× in this paper · explained in 2 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Ambient Dimension — 1× in this paper · explained in 1 episode
• Approximate Counting — 1× in this paper · explained in 1 episode
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Deterministic Optimistic Optimization — 1× in this paper
• Distribution Shift — 1× in this paper · explained in 6 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Geometric Distribution — 1× in this paper · explained in 2 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Local Optimization — 1× in this paper · explained in 2 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Online Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Structural Constraints — 1× in this paper · explained in 2 episodes
• Test-time Scaling — 1× in this paper · explained in 2 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
• Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

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