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Two-Level Softmax Sampling Done Right: Correcting Bias from Size Imbalance and Dispersion
Sampling from a softmax distribution is a fundamental operation in machine learning, but its linear complexity in the number of items makes exact sampling impractical at scale. Two-level softmax (2LS) sampling is a popular alternative enabling sublinear-time sampling. Assuming items are partitioned
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