Unverified50% confidenceFactExact time
When the target distribution has finite support, the paper gives an explicit particle count threshold, beyond which no spurious local minima exist and every spurious stationary point is unstable.
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10/15/2026
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Related Claims
UnverifiedThe optimization problem of weighted MMD is non-convex, and when the number of particles is insufficient, gradient flow easily falls into spurious local minima.73% similarUnverifiedThe paper designs an explicit target density that lowers probability mass near undesirable conditions, with the strength of the suppression controlled by a parameter.72% similarUnverified浮点数在token空间中并非连续分布，导致LLM精确运算天然不可靠71% similarUnverifiedFor any compactly supported target distribution, as long as the number of particles is sufficiently large, the MMD at every local minimum in the weighted MMD optimization landscape can be arbitrarily small.70% similarUnverifiedThe paper requires the algebraic complete intersection to have a specified dimension, bounded degree, and bounded condition number; this restriction sets a threshold for computability and statistical stability, at the cost that the hypothesis class is narrowed and may fail to cover some real complex data distributions.66% similar
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