Posts tagged "Bandits"

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Notes on "From Predictions to Decisions" (Wen et al., 2022)

August 12, 2026 • bayesian statistics, machine learning, bandits, statistical methods

Wen et al. show two forecasters with identical marginal predictions can make arbitrarily different decisions. A disjoint contextual bandit (one model per arm) is exactly their independence forecaster. In conjugate linear models the joint is exact and free, and partial pooling through a shared component gets it back.

Notes on "Deep Bayesian Bandits Showdown" (Riquelme et al., 2018)

January 31, 2026 • bayesian statistics, machine learning, bandits, statistical methods

I probably overuse the normal-inverse-gamma posterior. Every time I build a bandit system, every time I need uncertainty quantification for sequential decisions, I end up back at conjugate linear regression.