Results 31 to 40 of about 8,311,474 (361)

Some Multisecret-Sharing Schemes over Finite Fields

open access: yesMathematics, 2020
A secret sharing scheme is a method of assigning shares for a secret to some participants such that only some distinguished subsets of these subsets can recover the secret while other subsets cannot.
Selda Çalkavur, Patrick Solé
doaj   +1 more source

Practical challenges in data‐driven interpolation: Dealing with noise, enforcing stability, and computing realizations

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley   +1 more source

Traversing Knowledge Graphs in Vector Space [PDF]

open access: yesConference on Empirical Methods in Natural Language Processing, 2015
Path queries on a knowledge graph can be used to answer compositional questions such as "What languages are spoken by people living in Lisbon?". However, knowledge graphs often have missing facts (edges) which disrupts path queries.
Kelvin Guu, John Miller, Percy Liang
semanticscholar   +1 more source

Data‐driven performance metrics for neural network learning

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri   +2 more
wiley   +1 more source

A Vector Space for Distributional Semantics for Entailment [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2016
Distributional semantics creates vector-space representations that capture many forms of semantic similarity, but their relation to semantic entailment has been less clear.
James Henderson, Diana Nicoleta Popa
semanticscholar   +1 more source

Bochner integrals in ordered vector spaces [PDF]

open access: yes, 2016
We present a natural way to cover an Archimedean directed ordered vector space $E$ by Banach spaces and extend the notion of Bochner integrability to functions with values in $E$.
van Rooij, Arnoud, van Zuijlen, Willem
core   +3 more sources

The Linear Space of Hausdorff Continuous Interval Functions

open access: yesBiomath, 2013
In this paper we discuss the algebraic structure of the space H(X) of finite Hausdorff continuous interval functions defined on an arbitrary topological space X.
Jan Harm van der Walt
doaj   +1 more source

On Characterization of δ-Topological Vector Space

open access: yesRatio Mathematica, 2021
The main objective of this paper is to present the study of δ-topological vector space, δ-topological vector space are defined by using δ-open sets and δ-continuous mapping which was introduced by J.H.H. Bayati[3] in 2019. In this paper, along with basic
Shallu Sharma   +2 more
doaj   +1 more source

On the Vector in Homogeneous Spaces [PDF]

open access: yesNagoya Mathematical Journal, 1953
The main purpose of this paper is to investigate the parallelism of vectors in homogeneous spaces. The definition of a vector and the condition for spaces under which a covariant differential of a vector is also a vector were given by E. Cartan [4] in a very intuitive way. Here I formulate this in a stricter way by his method of moving frame. Even if a
openaire   +4 more sources

Compositional Vector Space Models for Knowledge Base Completion [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2015
Knowledge base (KB) completion adds new facts to a KB by making inferences from existing facts, for example by inferring with high likelihood nationality(X,Y) from bornIn(X,Y).
Arvind Neelakantan   +2 more
semanticscholar   +1 more source

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