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Entropy Transformation Measures for Computational Capacity
Kernel Rank and Generalization Rank are common measures used to characterise reservoir computing systems. However, there are some common issues in...
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Sparse low-rank approximation of matrix and local preservation for unsupervised image feature selection
Generalized low-rank approximation of matrix (GLRAM) is a multi-linear learning method and has been widely concerned due to its outstanding...
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Learning to Jointly Transform and Rank Difficult Queries
Recent empirical studies have shown that while neural rankers exhibit increasingly higher retrieval effectiveness on tasks such as ad hoc retrieval,...
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Low-rank approximation-based bidirectional linear discriminant analysis for image data
Dimensionality reduction methods for images directly without matrix-to-vector conversion have been widely concerned and achieved good classification...
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Effective Lower Bounds on the Matrix Rank and Their Applications
AbstractWe propose an efficiently verifiable lower bound on the rank of a sparse fully indecomposable square matrix that contains two non-zero...
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Lower Bounds for the Rank of a Matrix with Zeros and Ones outside the Leading Diagonal
AbstractWe found a lower bound on the rank of a square matrix where every entry in the leading diagonal is neither zero nor one and every entry...
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Learning to Rank in Session-Based Recommender Systems
Today, our daily activities are increasingly dependent on data-oriented systems. A new trend emerged based on machine learning techniques to rank the...
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Upper Bounds on Communication in Terms of Approximate Rank
We show that any Boolean function with approximate rank r can be computed by bounded-error quantum protocols without prior entanglement of complexity
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Laplacian regularized deep low-rank subspace clustering network
Self-expression-based deep subspace clustering, integrating traditional subspace clustering methods into deep learning paradigm to enhance the...
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Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems
Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries,...
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Injective Rank Metric Trapdoor Functions with Homogeneous Errors
In rank-metric cryptography, a vector from a finite dimensional linear space over a finite field is viewed as the linear space spanned by its...
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TS Fuzzy Model Transformation
The Chapter introduces the TS Fuzzy model transformation. In the related literature the term of the TP model transformation is used very frequently....
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Low-Rank Tensor Decomposition
Infrared small target detection is a research hotspot in computer vision technology that plays an important role in infrared early warning systems....
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A complex structure-preserving algorithm for the full rank decomposition of quaternion matrices and its applications
In this paper, based on the Gauss transformation of a quaternion matrix, we study the full rank decomposition of a quaternion matrix, and obtain a...
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Image classification based on weighted nonconvex low-rank and discriminant least squares regression
Classifiers based on least squares regression (LSR) are effective in multi-classification tasks. However, there are two main problems that greatly...
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Using Application Conditions to Rank Graph Transformations for Graph Repair
When using graphs and graph transformations to model systems, consistency is an important concern. While consistency has primarily been viewed as a...
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An in-depth study on adversarial learning-to-rank
In light of recent advances in adversarial learning, there has been strong and continuing interest in exploring how to perform adversarial...
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Modified correlated total variation regularization for low-rank matrix recovery
Image data often suffer from evident degradation like corruptions and missing values due to the defects of image acquisition equipment. Low-Rank...
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Building MPCitH-Based Signatures from MQ, MinRank, and Rank SD
The MPC-in-the-Head paradigm is a useful tool to build practical signature schemes. Many such schemes have been already proposed, relying on...
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TP Model Transformation
The chapter introduces the concept and the numerical reconstruction of the TP model transformation. The numerical reconstruction is derived based on...