论文标题
一般数据分析与视觉信息分析应用的应用：可证明的t-Algebra上的可证明的向后兼容的半神范式
General Data Analytics with Applications to Visual Information Analysis: A Provable Backward-Compatible Semisimple Paradigm over T-Algebra
论文作者
论文摘要
我们考虑了在最近报告的半神经代数（称为T-Algebra）上的一般数据分析的新型向后兼容范式。我们通过通过固定尺寸的多路阵列和T-Elgebra的元素来代表T-代数的元素来研究T-Algebra上的抽象代数框架，并通过收集的直接产品组成部分来研究T-Elgeba的元素。在T-Elgebra上，使用这种新的半圣范式以直接的方式概括了许多算法。为了展示新的范式的性能及其向后兼容性，我们概括了一些规范算法进行视觉模式分析。公共数据集上的实验表明，广义算法与其规范对应物相比有利。
We consider a novel backward-compatible paradigm of general data analytics over a recently-reported semisimple algebra (called t-algebra). We study the abstract algebraic framework over the t-algebra by representing the elements of t-algebra by fix-sized multi-way arrays of complex numbers and the algebraic structure over the t-algebra by a collection of direct-product constituents. Over the t-algebra, many algorithms are generalized in a straightforward manner using this new semisimple paradigm. To demonstrate the new paradigm's performance and its backward-compatibility, we generalize some canonical algorithms for visual pattern analysis. Experiments on public datasets show that the generalized algorithms compare favorably with their canonical counterparts.
