Sparse nested Markov models with log-linear parameters by Shpitser, I, Evans, R, Richardson, T, Robins, J

“…Placing such limits is similar in spirit to sparsity methods for undirected graphical models, and regression models. …”

An efficient and accurate decomposition of the Fermi operator. by Ceriotti, M, Kühne, T, Parrinello, M

“…It lends itself naturally to linear scaling as soon as the sparsity of the system's density matrix is exploited. …”

COSMO: A conic operator splitting method for convex conic problems by Garstka, M, Cannon, M, Goulart, P

“…Moreover, the solver uses chordal decomposition techniques and a new clique merging algorithm to effectively exploit sparsity in large, structured semidefinite programs. …”

On Sparse‚ Spectral and Other Parameterizations of Binary Probabilistic Models by Buchman, D, Schmidt, M, Mohamed, S, Poole, D, de Freitas, N

“…We show that the spectral parameterization, along with the canonical, has the best performance and sparsity levels, while the spectral does not depend on any particular reference state. …”

<italic>I</italic>_{<italic>ϵ</italic>+}LGEA: A Learning-Guided Evolutionary Algorithm Based on <italic>I</italic>_{<italic>ϵ</italic>+} Indicator for Portfolio Opt... by Feng Wang, Zilu Huang, Shuwen Wang

“…The new model has practical constraints which involve the sparsity and irregularity of variables and make it challenging to be solved by traditional Multi-Objective Evolutionary Algorithms (MOEAs). …”
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A Sparse Denoising-Based Super-Resolution Method for Scanning Radar Imaging by Qiping Zhang, Yin Zhang, Yongchao Zhang, Yulin Huang, Jianyu Yang

“…However, for some targets with typical shapes, the strong sparsity of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>1</mn></msub></semantics></math></inline-formula> norm treats them as strong-point targets, resulting in the loss of shape characteristics. …”
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Sparse Macro-track Transport Acceleration Method for 3-D Pebble-bed Geometry by GUO Jian1, GUO Jiong2, LI Fu2, YAN Rui1, ZOU Yang1

“…Excellent speedup ratio can be obtained by setting the sparsity to 3-5, the macro-track length to around 2.0 cm, the acceleration iteration steps limit to 20-60. …”
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Performance Analysis of Sparse Matrix-Vector Multiplication (SpMV) on Graphics Processing Units (GPUs) by Sarah AlAhmadi, Thaha Mohammed, Aiiad Albeshri, Iyad Katib, Rashid Mehmood

“…No single SpMV storage or computation scheme provides consistent and sufficiently high performance for all matrices due to their varying sparsity patterns. An extensive literature review reveals that the performance of SpMV techniques on GPUs has not been studied in sufficient detail. …”
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On the Relationship Between Universal Adversarial Attacks and Sparse Representations by Dana Weitzner, Raja Giryes

“…In this article, we aim at explaining this vulnerability through the framework of sparsity. We show the connection between adversarial attacks and sparse representations, with a focus on explaining the universality and transferability of adversarial examples in neural networks. …”
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Anomaly Detection in Multichannel Data Using Sparse Representation in RADWT Frames by Daniela De Canditiis, Italia De Feis

“…Then we perform AD imposing a double penalty on the multiple regression model we obtained, promoting group sparsity both on the regression coefficients and on the anomalies. …”
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Sparse Damage Detection with Complex Group Lasso and Adaptive Complex Group Lasso by Vasileios Dimopoulos, Wim Desmet, Elke Deckers

“…Sparsity-based methods have recently come to the foreground of damage detection applications posing a robust and efficient alternative for traditional approaches. …”
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A New Framework for the Harmonic Balance Method in OpenFOAM by Stefano Oliani, Nicola Casari, Mauro Carnevale

“…The Harmonic Balance Method is one of the most commonly employed Reduced Order Models for turbomachinery calculations, since it leverages the signal sparsity in the frequency domain to cast the transient equations into a coupled set of steady-state ones. …”
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Finite-rate sparse quantum codes aplenty by Maxime Tremblay, Guillaume Duclos-Cianci, Stefanos Kourtis

“…This framework allows us to enforce stabilizer commutation, $X/Z$ balancing, finite rate, sparsity, and maximum-degree constraints simultaneously in a CSP that we can then solve numerically. …”
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A Matlab Toolbox for Extended Dynamic Mode Decomposition Based on Orthogonal Polynomials and p-q Quasi-Norm Order Reduction by Camilo Garcia-Tenorio, Alain Vande Wouwer

“…An important question at this stage is the selection of basis functions to construct the observable functions, which in turn is determinant of the sparsity and efficiency of the approximation. In this study, attention is focused on orthogonal polynomial expansions and an order-reduction procedure called p-q quasi-norm reduction. …”
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Less is More: Mitigate Spurious Correlations for Open-Domain Dialogue Response Generation Models by Causal Discovery by Tao Feng, Lizhen Qu, Gholamreza Haffari

“…The classifier is trained by a constrained self-training method, coined ConSTrain, to overcome data sparsity. The experimental results based on both human and automatic evaluation show that our method significantly outperforms the competitive baselines in terms of relevance, informativeness, and fluency.…”
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G2S3: A gene graph-based imputation method for single-cell RNA sequencing data. by Weimiao Wu, Yunqing Liu, Qile Dai, Xiting Yan, Zuoheng Wang

“…However, prevalent dropout events result in high data sparsity and noise that may obscure downstream analyses in single-cell transcriptomic studies. …”
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A New Hybrid Collaborative Recommender Using Semantic Web Technology and Demographic data by Faezeh Sadat Gohari, Mohammad Jafar Tarokh

“…Regardless of its success in many application domains, CF has main limitations such as sparsity, scalability and new user/item problems. As new direction, semantic-based recommenders have emerged that deal with the semantic information of items. …”
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Resource Allocation for Network Slicing in RAN Using Case-Based Reasoning by Dandan Yan, Xu Yang, Laurie Cuthbert

“…In the matching process, the k-nearest neighbors (KNN) algorithm is used to retrieve similar cases, the nearest <i>k</i> neighbors being determined by considering sparsity reduction and locality-preserving projections. …”
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A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System by Hassan Abdullah Kubba, Yasser Falah Hassan

“…The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gives reduction in overall computation time and storage requirements. …”
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Pragmatic Micrometre to Millimetre Calibration Using Multiple Methods for Low-Coherence Interferometer in Embedded Metrology Applications by Tom Hovell, Jon Petzing, Laura Justham, Peter Kinnell

“…Additionally, the impact of dataset sparsity is shown along with the effect of using a singular calibration dataset for system performance when operating across different media.…”
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