Rethinking Learnability in Offline Data-driven Optimization

arXiv:2609.01493 · cs.LG, cs.AI, cs.NE · Submitted 2026-09-01 · Read on arXiv

cs.LG, cs.AI, cs.NE

Submitted: 2026-09-01

Updated: 2026-09-02

Terminology

• Diffusion Model — 18× in this paper · explained in 8 episodes
• Black-Box Optimization — 12× in this paper
• Objective Function — 12× in this paper · explained in 2 episodes
• Regret — 12× in this paper · explained in 3 episodes
• Bayesian Optimization — 11× in this paper · explained in 3 episodes
• Adam — 8× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Transformer — 6× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Probably Approximately Correct — 3× in this paper
• Regularization — 3× in this paper · explained in 3 episodes
• Sample Complexity — 3× in this paper · explained in 15 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Acquisition Function — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 4 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Multi-objective Optimization — 2× in this paper · explained in 4 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Uncertainty-aware Gradient-guided Trajectory Learning — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptive Sampling — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Distribution Matching — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Probably Mostly Approximately Correct — 1× in this paper
• Steering — 1× in this paper · explained in 2 episodes

Sources

• OpenAI Gym
• The CMA Evolution Strategy: A Tutorial
• On the Learnability of Offline Model-Based Optimization: A Ranking Perspective

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