Results 41 to 50 of about 496,714 (284)
Anticodes in the sum-rank metric
Linear Algebra and its Applications, 2022 We study the structure of anticodes in the sum-rank metric for arbitrary fields and matrix blocks of arbitrary sizes. Our main result is a complete classification of optimal linear anticodes. We also compare the cardinality of the ball in the sum-rank metric with that of an optimal linear anticode, showing that the latter is strictly larger over ...
Eimear Byrne +2 more
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IEEE Access, 2023 Attribute-based encryption is a valuable technique for ensuring data privacy and confidentiality in the realm of cloud computing. Using this cryptographic primitive, the data owner can securely store and share data within the cloud environment.
Vahid Yousefipoor, Taraneh Eghlidos
doaj +1 more source
Geometry, conformal Killing-Yano tensors and conserved “currents”
Journal of High Energy Physics, 2023 In this paper we discuss the construction of conserved tensors (currents) involving conformal Killing-Yano tensors (CKYTs), generalising the corresponding constructions for Killing-Yano tensors (KYTs).
Ulf Lindström, Özgür Sarıoğlu
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Comparing Fair Ranking Metrics
, 2020 Ranked lists are frequently used by information retrieval (IR) systems to present results believed to be relevant to the users information need. Fairness is a relatively new but important aspect of these rankings to measure, joining a rich set of metrics that go beyond traditional accuracy or utility constructs to provide a more holistic understanding ...
Raj, Amifa, Ekstrand, Michael D.
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Supervised Learning Using Homology Stable Rank Kernels
Frontiers in Applied Mathematics and Statistics, 2021 Exciting recent developments in Topological Data Analysis have aimed at combining homology-based invariants with Machine Learning. In this article, we use hierarchical stabilization to bridge between persistence and kernel-based methods by introducing ...
Jens Agerberg +4 more
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Relevance Ranking Metrics for Learning Objects [PDF]
IEEE Transactions on Learning Technologies, 2007 This paper develops the concept of relevance in the context of learning object search. It proposes a set of metrics to estimate the topical, personal and situational relevance dimensions. These metrics are derived mainly from usage and contextual information.
Ochoa, Xavier, Duval, Erik
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background While Wilms tumor (WT) typically has a favorable prognosis, relapsed cases—especially those with high‐risk histology—remain therapeutically challenging after intensive frontline therapy. The combination of vincristine and irinotecan has demonstrated activity in pediatric solid tumors, and pazopanib, a multi‐targeted tyrosine kinase ...
Maria Debora De Pasquale +6 more
wiley +1 more source
Intelligent Recommender System for Big Data Applications Based on the Random Neural Network
Big Data and Cognitive Computing, 2019 Online market places make their profit based on their advertisements or sales commission while businesses have the commercial interest to rank higher on recommendations to attract more customers.
Will Serrano
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On the List-Decodability of Random Linear Rank-Metric Codes
, 2017 The list-decodability of random linear rank-metric codes is shown to match that of random rank-metric codes. Specifically, an $\mathbb{F}_q$-linear rank-metric code over $\mathbb{F}_q^{m \times n}$ of rate $R = (1-\rho)(1-\frac{n}{m}\rho)-\varepsilon$ is
Guruswami, Venkatesan, Resch, Nicolas
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Pediatric Blood &Cancer, EarlyView.ABSTRACT We sought to identify potential early risk biomarkers for lung disease in children post‐allogeneic HCT. Patients with pulmonary function tests 3 months post‐transplant and plasma samples between days 7 and 14 post‐HCT were included. Six of 27 subjects enrolled had reduced forced expiratory volume 1 (FEV1) z scores.
Isabella S. Small +3 more
wiley +1 more source