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Anomaly Detection Based on Convex Analysis: A Survey
Frontiers in Physics, 2022 As a crucial technique for identifying irregular samples or outlier patterns, anomaly detection has broad applications in many fields. Convex analysis (CA) is one of the fundamental methods used in anomaly detection, which contributes to the robust ...
Tong Wang +8 more
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Sharpening Sparse Regularizers via Smoothing
IEEE Open Journal of Signal Processing, 2021 Non-convex sparsity-inducing penalties outperform their convex counterparts, but generally sacrifice the cost function convexity. As a middle ground, we propose the sharpening sparse regularizers (SSR) framework to design non-separable non-convex ...
Abdullah H. Al-Shabili +2 more
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Sparse Regularized Optimal Transport with Deformed q-Entropy
Entropy, 2022 Optimal transport is a mathematical tool that has been a widely used to measure the distance between two probability distributions. To mitigate the cubic computational complexity of the vanilla formulation of the optimal transport problem, regularized ...
Han Bao, Shinsaku Sakaue
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AutoBar: Automatic Barrier Coverage Formation for Danger Keep Out Applications in Smart City
Sensors, 2023 Barrier coverage is a fundamental application in wireless sensor networks, which are widely used for smart cities. In applications, the sensors form a barrier for the intruders and protect an area through intrusion detection.
Ying Shao +8 more
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New Journal of Physics, 2023 Motivated by the Penrose–Onsager criterion for Bose–Einstein condensation we propose a functional theory for targeting low-lying excitation energies of bosonic quantum systems through the one-particle picture.
Julia Liebert, Christian Schilling
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On the sufficiency of K-positivity for truncated compactly supported generalized moment problems
Examples and Counterexamples, 2021 Given a compact set K and a finite set of continuous basis functions, the truncated generalized K-moment problem asks for a characterization of all sequences that can be obtained as moments, with respect to the basis functions, of some nonnegative ...
Axel Ringh
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General optimal euclidean Sobolev and Gagliardo-Nirenberg inequalities
Anais da Academia Brasileira de Ciências, 2005 We prove general optimal euclidean Sobolev and Gagliardo-Nirenberg inequalities by using mass transportation and convex analysis results. Explicit extremals and the computation of some optimal constants are also provided.
Jurandir Ceccon, Marcos Montenegro
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AN EFFICIENT ALGORITHM FOR THE CONVEX HULL OF PLANAR SCATTERED POINT SET [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Computing the convex hull of a point set is requirement in the GIS applications. This paper studies on the problem of minimum convex hull and presents an improved algorithm for the minimum convex hull of planar scattered point set.
Z. Fu, Y. Lu
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On the enumeration of column-convex permutominoes [PDF]
Discrete Mathematics & Theoretical Computer Science, 2011 We study the enumeration of \emphcolumn-convex permutominoes, i.e. column-convex polyominoes defined by a pair of permutations. We provide a direct recursive construction for the column-convex permutominoes of a given size, based on the application of ...
Nicholas R. Beaton +3 more
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HPPD: A Hybrid Parallel Framework of Partition-based and Density-based Clustering Algorithms in Data Streams [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2020 Data stream clustering refers to the process of grouping continuously arriving new data chunks into continuously changing groups to enable dynamic analysis of segmentation patterns.
Ammar Abd Alazeez
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