Unverified50% confidenceFactExact time
The BROJA scheme, proposed by Bertschinger, Rauh, Olbrich, Jost, and Ay, defines redundant information via a constrained optimization problem by searching, among all joint distributions satisfying specific marginal constraints, for the distribution that maximizes redundant information.
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10/12/2026
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UnverifiedPrior research has shown that when each pairwise source–target variable joint distribution follows a Gaussian distribution, the BROJA optimization problem can be reduced to a finite-dimensional numerical optimization problem.70% similarUnverifiedAutoregressive generation has three fundamental limitations: sequential dependency, information bottleneck, and error accumulation.60% similarUnverifiedUCB算法和汤普森采样通过为每个选项构建置信区间上界来量化不确定性，平衡利用与探索，在理论上达到遗憾的对数上界60% similarUnverifiedImplicit solving requires solving a system of linear equations, with each step requiring second-order information similar to the Hessian or its approximation, resulting in enormous computational and storage overhead at the scale of millions or billions of parameters.60% similarUnverifiedTraditional first-order Langevin algorithms (such as projected Langevin Monte Carlo) require that the log-density of the target distribution be differentiable when handling sampling on constrained domains.60% similar
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