Results 31 to 40 of about 335,764 (251)
The Deterministic Information Bottleneck [PDF]
Neural Computation, 2017 Lossy compression and clustering fundamentally involve a decision about which features are relevant and which are not. The information bottleneck method (IB) by Tishby, Pereira, and Bialek ( 1999 ) formalized this notion as an information-theoretic optimization problem and proposed an optimal trade-off between throwing away as many bits as possible ...
Strouse, Daniel J., Schwab, David J.
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Embo: a Python package for empirical data analysis using the Information Bottleneck
Journal of Open Research Software, 2021 We present 'embo', a Python package to analyze empirical data using the Information Bottleneck (IB) method and its variants, such as the Deterministic Information Bottleneck (DIB).
Eugenio Piasini +3 more
doaj +1 more source
Heterogeneous Graph Information Bottleneck [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 Most attempts on extending Graph Neural Networks (GNNs) to Heterogeneous Information Networks (HINs) implicitly take the direct assumption that the multiple homogeneous attributed networks induced by different meta-paths are complementary. The doubts about the hypothesis of complementary motivate an alternative assumption of consensus. That is, the
Liang Yang +7 more
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The Information Bottleneck's Ordinary Differential Equation: First-Order Root Tracking for the Information Bottleneck. [PDF]
Entropy (Basel), 2023 The Information Bottleneck (IB) is a method of lossy compression of relevant information. Its rate-distortion (RD) curve describes the fundamental tradeoff between input compression and the preservation of relevant information embedded in the input. However, it conceals the underlying dynamics of optimal input encodings.
Agmon S.
europepmc +4 more sources
Recognizable Information Bottleneck
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Information Bottlenecks (IBs) learn representations that generalize to unseen data by information compression. However, existing IBs are practically unable to guarantee generalization in real-world scenarios due to the vacuous generalization bound. The recent PAC-Bayes IB uses information complexity instead of information compression to establish a ...
Lyu, Yilin +6 more
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Collaborative Information Bottleneck [PDF]
IEEE Transactions on Information Theory, 2019 Submitted to IEEE Transactions on Information Theory (revised, 29, 7 figures)
Matias Vera +2 more
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Variational Information Bottleneck for Semi-Supervised Classification
Entropy, 2020 In this paper, we consider an information bottleneck (IB) framework for semi-supervised classification with several families of priors on latent space representation. We apply a variational decomposition of mutual information terms of IB.
Slava Voloshynovskiy +4 more
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Learnability for the Information Bottleneck
Entropy, 2019 The Information Bottleneck (IB) method provides an insightful and principled approach for balancing compression and prediction for representation learning. The IB objective I ( X ; Z ) - β I ( Y ; Z ) employs a Lagrange multiplier β
Tailin Wu +3 more
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Objective Classification of Galaxy Spectra using the Information Bottleneck Method [PDF]
, 2000 A new method for classification of galaxy spectra is presented, based on a recently introduced information theoretical principle, the `Information Bottleneck'.
Bell +5 more
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Where are Bottlenecks in NK Fitness Landscapes? [PDF]
, 2003 Usually the offspring-parent fitness correlation is used to visualize and analyze some caracteristics of fitness landscapes such as evolvability. In this paper, we introduce a more general representation of this correlation, the Fitness Cloud (FC).
Clergue, Manuel +2 more
core +3 more sources