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Broadcast Product: Redefining Shape-aligned Element-wise ...
[Submitted on 26 Sep 2024 (v1), last revised 16 Jun 2026 (this v · 2026-06-17 · via cs.LG updates on arXiv.org

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Abstract:Broadcast operations are widely used in scientific computing libraries, yet their mathematical formulation is often implicit and inconsistently represented in machine learning literature. This problem frequently leads to invalid equations when element-wise products are written despite mismatched tensor shapes. In this paper, we formalize such operations by introducing the broadcast product $\boxdot$, which explicitly extends the Hadamard product through shape-aligned element duplication. We provide a rigorous definition of the broadcast product, analyze its algebraic properties, and show how it can be expressed using standard linear algebra. Building on this framework, we formulate least-squares problems and sketch a proof-of-concept broadcast decomposition. As a preliminary illustration, we show that the formalism enables a new family of decompositions with distinct structural properties from conventional tensor decompositions. This work establishes a mathematical foundation for broadcast-aware tensor operations, connecting practical implementations with rigorous tensor analysis.

Submission history

From: Yusuke Matsui [view email]
[v1] Thu, 26 Sep 2024 03:20:09 UTC (518 KB)
[v2] Tue, 16 Jun 2026 16:16:25 UTC (599 KB)