Explore how Thompson Sampling with AI transforms search optimization in fields like protein design and question answering. What innovative applications do you see for AI in your industry? Let’s discuss! #AI #Innovation #ThompsonSampling LINK

Diffusion Approximations Reveal New Insights for Thompson Sampling

Researchers show in the small‑gap regime (gaps ~√γ) Thompson sampling updates converge to stochastic differential equations; latest now revision Oct 5 2025. getnews.me/diffusion-approximations... #thompsonsampling #diffusionapproximation

AI Thompson Sampling Drives Nash Equilibrium, Avoids Collusion

Research shows two agents using Thompson sampling converge to the Nash equilibrium, avoiding algorithmic collusion when every action has a non‑zero chance of being optimal. Read more: getnews.me/ai-thompson-sampling-dri... #thompsonsampling #nash

New Methods Improve Prior Selection for Gaussian Process Bandits

Two new GP‑Thompson sampling variants—Prior‑Elimination GP‑TS (PE‑GP‑TS) and HyperPrior GP‑TS (HP‑GP‑TS)—adaptively select priors and achieve sub‑linear regret, reported on 26 Sep 2025. getnews.me/new-methods-improve-prio... #gpbands #thompsonsampling

Bayesian Algorithms for Adversarial Online Learning in Infinite Actions

Researchers propose a Thompson sampling that uses a Gaussian‑process prior on the d‑dimensional unit cube [0,1]^d and achieves a regret bound of O(β√(Td log(1+√d λ/β))). getnews.me/bayesian-algorithms-for-... #thompsonsampling #gaussianprocess