Results 11 to 20 of about 567,556 (268)
Hierarchical algorithms on hierarchical architectures [PDF]
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2020 A traditional goal of algorithmic optimality, squeezing out flops, has been superseded by evolution in architecture. Flops no longer serve as a reasonable proxy for all aspects of complexity. Instead, algorithms must now squeeze memory, data transfers, and synchronizations, while extra flops on locally cached data represent only small costs in time and
D. E. Keyes, H. Ltaief, G. Turkiyyah
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Hierarchical isometry properties of hierarchical measurements
Applied and Computational Harmonic Analysis, 2022 Compressed sensing studies linear recovery problems under structure assumptions. We introduce a new class of measurement operators, coined hierarchical measurement operators, and prove results guaranteeing the efficient, stable and robust recovery of hierarchically structured signals from such measurements.
Axel Flinth +4 more
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Hierarchical and non-hierarchical mineralisation of collagen [PDF]
Biomaterials, 2011 Biomineralisation of collagen involves functional motifs incorporated in extracellular matrix protein molecules to accomplish the objectives of stabilising amorphous calcium phosphate into nanoprecursors and directing the nucleation and growth of apatite within collagen fibrils.
Yan, Liu +6 more
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Journal of Computer and Communications, 2023 Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is this idea that leads the integration of hierarchical dimensions into these responses.
Martin Nevot, Mickaël +2 more
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The Construction of Hierarchic and Non-Hierarchic Classifications [PDF]
The Computer Journal, 1968 Many of the cluster methods that are used in the construction of classificatory systems operate on data in the form of a dissimilarity coefficient on a set of objects. In this paper we outline a theoretical framework within which the properties of such methods may be discussed.
N. Jardine, Robin Sibson
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Distributed hierarchical SVD in the Hierarchical Tucker format [PDF]
Numerical Linear Algebra with Applications, 2018 SummaryWe consider tensors in the Hierarchical Tucker format and suppose the tensor data to be distributed among several compute nodes. We assume the compute nodes to be in a one‐to‐one correspondence with the nodes of the Hierarchical Tucker format such that connected nodes can communicate with each other.
Lars Grasedyck, Christian Löbbert
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Hierarchical models as marginals of hierarchical models
International Journal of Approximate Reasoning, 2017 We investigate the representation of hierarchical models in terms of marginals of other hierarchical models with smaller interactions. We focus on binary variables and marginals of pairwise interaction models whose hidden variables are conditionally independent given the visible variables. In this case the problem is equivalent to the representation of
Guido Montúfar, Johannes Rauh
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Expert Systems with Applications, 2011 In this paper, a new machine learning solution for function approximation is presented. It combines many simple and relatively inaccurate estimators to achieve high accuracy. It creates - in incremental manner - hierarchical, tree-like structure, adapting it to the specific problem being solved.
Brodowski, Stanisław, Podolak, Igor
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On Hierarchical Propositions [PDF]
Journal of Philosophical Logic, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Are "Hierarchical" Visual Representations Hierarchical?
CoRR, 2023 Learned visual representations often capture large amounts of semantic information for accurate downstream applications. Human understanding of the world is fundamentally grounded in hierarchy. To mimic this and further improve representation capabilities, the community has explored "hierarchical" visual representations that aim at modeling the ...
Ethan Shen, Ali Farhadi, Aditya Kusupati
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