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New methods correct biases in large-scale softmax sampling

By PulseAugur Editorial · [2 sources] ·

Researchers have identified systematic biases in the two-level softmax (2LS) sampling method, a technique used for efficient sampling from large distributions. The biases arise from ignoring cluster size imbalance and intra-cluster similarity dispersion. To address this, two new methods, Size-Corrected 2LS (S-2LS) and Size- and Dispersion-Corrected 2LS (SD-2LS), have been proposed. These methods offer provably better approximations of softmax distributions with minimal computational overhead, as validated by experiments on large datasets. AI

IMPACT These corrected sampling methods could lead to more accurate and efficient machine learning models in applications requiring large-scale sampling.

RANK_REASON The cluster contains an academic paper detailing new methods for improving a machine learning sampling technique.

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New methods correct biases in large-scale softmax sampling

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The cluster contains an academic paper detailing new methods for improving a machine learning sampling technique.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Walid Bendada, Guillaume Salha-Galvan ·

    Two-Level Softmax Sampling Done Right: Correcting Bias from Size Imbalance and Dispersion

    arXiv:2610.10483v1 Announce Type: new Abstract: 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 alternati…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Guillaume Salha-Galvan ·

    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 it…

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