6,339 research outputs found
Hetero-manifold Regularisation for Cross-modal Hashing
Recently, cross-modal search has attracted considerable attention but remains a very challenging task because of the integration complexity and heterogeneity of the multi-modal data. To address both challenges, in this paper, we propose a novel method termed hetero-manifold regularisation (HMR) to supervise the learning of hash functions for efficient cross-modal search. A hetero-manifold integrates multiple sub-manifolds defined by homogeneous data with the help of cross-modal supervision information. Taking advantages of the hetero-manifold, the similarity between each pair of heterogeneous data could be naturally measured by three order random walks on this hetero-manifold. Furthermore, a novel cumulative distance inequality defined on the hetero-manifold is introduced to avoid the computational difficulty induced by the discreteness of hash codes. By using the inequality, cross-modal hashing is transformed into a problem of hetero-manifold regularised support vector learning. Therefore, the performance of cross-modal search can be significantly improved by seamlessly combining the integrated information of the hetero-manifold and the strong generalisation of the support vector machine. Comprehensive experiments show that the proposed HMR achieve advantageous results over the state-of-the-art methods in several challenging cross-modal tasks
Continuous-variable controlled-Z gate using an atomic ensemble
The continuous-variable controlled-Z gate is a canonical two-mode gate for
universal continuous-variable quantum computation. It is considered as one of
the most fundamental continuous-variable quantum gates. Here we present a
scheme for realizing continuous-variable controlled-Z gate between two optical
beams using an atomic ensemble. The gate is performed by simply sending the two
beams propagating in two orthogonal directions twice through a spin-squeezed
atomic medium. Its fidelity can run up to one if the input atomic state is
infinitely squeezed. Considering the noise effects due to atomic decoherence
and light losses, we show that the observed fidelities of the scheme are still
quite high within presently available techniques.Comment: 7 pages, 3 figures, to appear in Physical Review
Research on the Application of Blockchain in SMEs Credit Risk
The credit of an enterprise is related to its own development. This paper mainly discusses the relationship between the credit risk of small and medium enterprises (SMEs) and the application degree of blockchain. 64 listed companies with block chain technology as the core theme are selected to analyze their comprehensive financial data. Factor analysis is used to quantitatively evaluate the application degree of blockchain in SMEs, and then the Logistic model is used to evaluate the credit risk of SMEs. Finally, combining the application degree of blockchain in small and medium-sized enterprises and the credit risk assessment of these two groups of data. It confirms the conclusion that the higher the degree of blockchain application, the closer the supply chain finance relationship, and the better the credit status
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