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Flow models for Generative AI
As an alternative to Diffusion Models, Continuous Normalizing Flow Matching is one of the most powerful paradigm for generative AI modeling.
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Optimal offline RL with the unified model-based framework
A model-based framework + singleton absorbing MDP technique achieves the optimal rate for several challenging offline tasks.
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A Brief Summary of Upper Bounds for Bandit Problems
This post summarizes the regret analysis of the Exploration-First Algorithm, the Upper Confidence Bound (UCB) Algorithm for the multi-armed bandits (MAB) problems and the LinUCB Algorithm for linear Bandits.
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A Brief Introduction to Influence Funtion Technique
Influence function technique is powerful in that it provides a way to calculate efficiency bound for the semiparameteric estimation problems.
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Variance Reduction Technique for Optimal Offline RL
A algorithm that achieves Minimax rate for tabular RL