Results 41 to 50 of about 24,894,856 (287)
The Effect of Evidence Transfer on Latent Feature Relevance for Clustering
Informatics, 2019 Evidence transfer for clustering is a deep learning method that manipulates the latent representations of an autoencoder according to external categorical evidence with the effect of improving a clustering outcome.
Athanasios Davvetas +3 more
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Frontiers in Neuroscience, 2023 As an important part of human cultural heritage, the recognition of genealogy layout is of great significance for genealogy research and preservation.
Jianing You, Qing Wang
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Decoding of Non-Binary LDPC Codes using the Information Bottleneck Method [PDF]
ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 2019 Recently, a novel lookup table based decoding method for binary low-density parity-check codes has attracted considerable attention. In this approach, mutual-information maximizing lookup tables replace the conventional operations of the variable nodes and the check nodes in message passing decoding.
Maximilian Stark +3 more
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Iranian Journal of Electrical and Electronic Engineering, 2021 Convolutional Neural Networks (CNNs) have been shown their performance in speech recognition systems for extracting features, and also acoustic modeling.
B. Nasersharif, N. Naderi
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Variational Information Bottleneck-Guided Complementary Concept Bottleneck Model [PDF]
Jisuanji kexue yu tansuoConcept bottleneck models (CBMs) project visual features extracted from black-box models onto a set of human-interpretable concepts to facilitate decision-making.
JI Zhong, LIN Zijie
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Variational Information Bottleneck for Unsupervised Clustering: Deep Gaussian Mixture Embedding
Entropy, 2020 In this paper, we develop an unsupervised generative clustering framework that combines the variational information bottleneck and the Gaussian mixture model.
Yiğit Uğur +2 more
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THE INFORMATION BOTTLENECK METHOD FOR OPTIMAL PREDICTION OF MULTILEVEL AGENT-BASED SYSTEMS [PDF]
Advances in Complex Systems, 2016 Because the dynamics of complex systems is the result of both decisive local events and reinforced global effects, the prediction of such systems could not do without a genuine multilevel approach. This paper proposes to found such an approach on information theory. Starting from a complete microscopic description of the system dynamics, we are looking
Robin Lamarche-Perrin +2 more
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Distributed clustering of categorical data using the information bottleneck framework
, 2017 We perform clustering of categorical data using the Information Bottleneck, (IB), framework at large scale. We examine the performance of existing solutions using multiple machine architectures.
Natasa Tagasovska +3 more
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, 2021 The celebrated information bottleneck (IB) principle of Tishby et al. has recently enjoyed renewed attention due to its application in the area of deep learning. This collection investigates the IB principle in this new context.
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Production and Manufacturing Research: An Open Access Journal, 2023 Throughput is an important parameter to evaluate production system performance. It is typically constrained by one or more resources referred to as ‘throughput bottlenecks’.
Anders Skoogh +4 more
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