Adaptive Bayes exactly tracks information over intrinsic time

arXiv:2607.08789 · cs.LG, cs.IT, math.IT, math.ST, stat.ML, stat.TH · Submitted 2026-06-26 · Read on arXiv

cs.LG, cs.IT, math.IT, math.ST, stat.ML, stat.TH

Submitted: 2026-06-26

Updated: 2026-08-26

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

Terminology

• Regret — 233× in this paper · explained in 3 episodes
• Verification — 21× in this paper · explained in 2 episodes
• Benchmark — 20× in this paper · explained in 2 episodes
• Trace — 18× in this paper · explained in 2 episodes
• Calibration — 10× in this paper · explained in 7 episodes
• Contextual Bandits — 9× in this paper · explained in 3 episodes
• Sparsity — 9× in this paper · explained in 4 episodes
• Adaptation — 8× in this paper · explained in 1 episode
• Conference on Learning Theory — 8× in this paper
• Core — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• alpha — 4× in this paper · explained in 1 episode
• Adaptivity — 3× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• In International Conference on Machine Learning — 3× in this paper
• Abstention — 2× in this paper · explained in 1 episode
• Adaptive Algorithm — 2× in this paper · explained in 1 episode
• Meta-learning — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Adversarial Robustness — 1× in this paper · explained in 3 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Influence Functions — 1× in this paper · explained in 2 episodes
• Information Gain — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Non-stationarity — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• A second order regret bound for NormalHedge
• Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It
• A Short Note on a Variant of the Squint Algorithm

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