cs.IT · 2026-06-10 · No. 19

Information Theory, 2026-06-10.

2 new papers in cs.IT. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Secure Aggregation with Top-K Sparsification in Decentralized Federated Learning

    Hengxuan Tang, Jinbao Zhu, Xiaohu Tang

    cs.IT · cs.CR · cs.LG

    Secure aggregation is a vital component for mitigating gradient leakage in federated learning, but its communication cost conventionally scales with the gradient dimension. This becomes prohibitive for large models and even more pronounced in decentralized federated learning with limited bandwidth and unreliable nodes. Top-K gradient sparsification is an effective approach to reduce communication by transmitting only a few entries of the full...

    arxiv.org/abs/2606.10780 · PDF

  2. 02

    Minimum Distortion Quantization with Specified Output Distribution

    Aolin Xu

    cs.IT · cs.AI · math.OC · math.ST

    We derive the optimal quantizer of a real-valued random variable $W$ with distribution $P_W$ such that 1) the distribution of the quantization output $X$ that can take $k$ values follows any specified distribution $P_X$ over $\{1,\ldots,k\}$, and 2) the minimum mean squared error (MMSE) of estimating $W$ from $X$ is minimized. It is shown that the optimal quantizer takes the form $X=σ\big(F_{σ^{-1}(X)}^{-1}(F_W(W))\big)$, where $σ$ is the...

    arxiv.org/abs/2606.10458 · PDF

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