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A Constructive Method to Maximize Entropy under Marginal Constraints
arXiv stat.TH0 views
arXiv:2601.09347v3 Announce Type: replace-cross Abstract: We study the problem of maximizing R{\'e}nyi entropy of order $2$ (equivalently, minimizing the index of coincidence) over the set of joint distributions with prescribed marginals. A closed-form optimizer is known under a feasibility condition on the marginals; we show that this condition is highly restrictive. We then provide an explicit construction of an optimal coupling for arbitrary marginals. Our approach characterizes the optimizer's structure and yields an iterative algorithm that terminates in finite time, returning an exact solution after at most $p-1$ updates, where $p$ is the number of rows.
Source:https://arxiv.org/abs/2601.09347PreviousTemporal difference learning adapts to incomplete coverage: an oracle inequality over subgraphsNextOn the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization
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