mlsanityData to 14 Oct 2026

Broadcast Channel Cooperative Gain: An Operational Interpretation of Partial Information Decomposition

arXiv 2502.10878 ↗First posted 15 Feb 2025cs.IT cs.AI cs.LGcited by 2

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Abstract (arXiv)

Partial information decomposition has recently found applications in biological signal processing and machine learning. Despite its impacts, the decomposition was introduced through an informal and heuristic route, and its exact operational meaning is unclear. In this work, we fill this gap by connecting partial information decomposition to the capacity of the broadcast channel, which has been well-studied in the information theory literature. We show that the synergistic information in the decomposition can be rigorously interpreted as the cooperative gain, or a lower bound of this gain, on the corresponding broadcast channel. This interpretation can help practitioners to better explain and expand the applications of the partial information decomposition technique.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 9 of its 44 references that are in the map. First posted on arXiv 15 Feb 2025.

Builds on

9 of 44 references.

References · 9

  1. 2023Quantifying & Modeling Multimodal Interactions: An Information Decomposition Frameworkcited by 83
  2. 2023Factorized Contrastive Learning: Going Beyond Multi-view Redundancycited by 75
  3. 2019A Novel Approach to the Partial Information Decompositioncited by 17
  4. 2023Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Datacited by 17
  5. 2014Exploration of synergistic and redundant information sharing in static and dynamical Gaussian systemscited by 16
  6. 2016Measuring multivariate redundant information with pointwise common change in surprisalcited by 13
  7. 2015Partial Information Decomposition as a Unified Approach to the Specification of Neural Goal Functionscited by 12
  8. 2022A Measure of the Complexity of Neural Representations based on Partial Information Decompositioncited by 11
  9. 2017Unique Information via Dependency Constraintscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.