Stochastic Linear Bandits with Partially Observed Actions

arXiv:2607.08971 · cs.LG, math.ST, stat.ML · Submitted 2026-07-09 · Read on arXiv

Gautam Dasarathy, Vineet Gattani, Lalit Jain

cs.LG, math.ST, stat.ML

Submitted: 2026-07-09

Code: https://github.com/gautamdasarathy/tofu-pov-arxiv

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

Terminology

• Regret — 111× in this paper · explained in 4 episodes
• Regret Bound — 12× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Fidelity — 5× in this paper · explained in 2 episodes
• Intrinsic Dimension — 5× in this paper · explained in 3 episodes
• Robustness — 4× in this paper · explained in 6 episodes
• Surrogate Model — 4× in this paper · explained in 3 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Contextual Bandit — 3× in this paper · explained in 2 episodes
• Contextual Bandits — 3× in this paper · explained in 3 episodes
• Error Decomposition — 3× in this paper · explained in 4 episodes
• Active Learning — 2× in this paper · explained in 6 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Matrix Completion — 2× in this paper · explained in 4 episodes
• Regret Guarantees — 2× in this paper · explained in 2 episodes
• Two-phase OFUL with Partially Observed Vectors — 2× in this paper
• Augmentation — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Regret Bounds — 1× in this paper · explained in 2 episodes
• Reward Structure — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 5 episodes

Sources

• Linear Bandits with Partially Observable Features
• Stochastic Linear Bandits with Hidden Low Rank Structure
• Sparse Stochastic Bandits
• Hyperbolicity constants for pants and relative pants graphs
• An Introduction to Matrix Concentration Inequalities

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