20 papers · ranked by Valyu relevance
Paris V. Giampouras, Athanasios A. Rontogiannis, Eleftherios Kofidis
—The so-called block-term decomposition (BTD) tensor model, especially in its rank-(Lr, Lr, 1) version, has been recently receiving increasing attention due to its enhanced ability of representing systems and signals that are composed of blocks of rank higher than one, a scenario encountered in numerous and diverse…
Zehui Liu, Qingsong Wang, Chunfeng Cui
Block Term Tensor Decomposition Authors: ['Zehui Liu' 'Qingsong Wang' 'Chunfeng Cui'] In this paper, we explore a specific optimization problem that combines a differentiable nonconvex function with a nondifferentiable function for multi-block variables, which is particularly relevant to tackle the multilinear…
Guangxi Li, Jinmian Ye, Haiqin Yang, Di Chen + 2 more
'Zenglin Xu'] Recently, deep neural networks (DNNs) have been regarded as the state-of-the-art classification methods in a wide range of applications, especially in image classification. Despite the success, the huge number of parameters blocks its deployment to situations with light computing resources. Researchers…
Ming Yang
We present several conditions for generic uniqueness of tensor decompositions of multilinear rank (1, L1, L1), · · · , (1, LR, LR) terms. In geometric language, we prove that the joins of relevant subspace varieties are not tangentially weakly defective. We also give conditions for partial uniqueness of block term…
Guoyong Zhang, Xiao Fu, Jun Wang, Xi-Le Zhao + 1 more
—Spectrum cartography aims at estimating power propagation patterns over a geographical region across multiple frequency bands (i.e., a radio map)—from limited samples taken sparsely over the region. Classic cartography methods are mostly concerned with recovering the aggregate radio frequency (RF) information while…
Manvel Gasparyan, Satya Tamby, G.V. HarshaRani, Upinder S. Bhalla + 1 more
Biochemical networks are models of biological functions and processes in biomedicine. Hierarchical decomposition simplifies complex biochemical networks by partitioning them into smaller blocks (modules), facilitating computationally intensive analyses and providing deeper insights into cellular processes and…
Manvel Gasparyan, Satya Tamby, G.V. HarshaRani, Upinder S. Bhalla + 1 more
Biochemical networks are models of biological functions and processes in biomedicine. Hierarchical decomposition simplifies complex biochemical networks by partitioning them into smaller blocks (modules), facilitating computationally intensive analyses and providing deeper insights into cellular processes and…
Xudong Li, Defeng Sun, Kim-Chuan Toh
For a symmetric positive semidefinite linear system of equations Qx = b, where x = (x1, . . . , xs) is partitioned into s blocks, with s ≥ 2, we show that each cycle of the classical block symmetric Gauss-Seidel (block sGS) method exactly solves the associated quadratic programming (QP) problem but added with an extra…
Eduardo Del Rio, Leonardo Oliveira
The Helmert-blocking technique is a common approach to adjust large geodetic networks like Europeans and Brazilians. The technique is based upon a division of the network into partial networks called blocks. This way, the global network adjustment can be done by manipulating these blocks. Here we show alternatives to…
Farnaz Sedighin, Andrzej Cichocki
Tensor Completion is an important problem in big data processing. Usually, data acquired from different aspects of a multimodal phenomenon or different sensors are incomplete due to different reasons such as noise, low sampling rate or human mistake. In this situation, recovering the missing or uncertain elements of…
Florian Privé
A few algorithms have been developed for splitting the genome in nearly independent blocks of linkage disequilibrium. Due to the complexity of this problem, these algorithms rely on heuristics, which makes them sub-optimal. Here we develop an optimal solution for this problem using dynamic programming. This is now…
Yan Du, Jun Peng, Dacheng Hu, Junhui Wang + 6 more
This paper introduces a method for estimating signal direction of arrival (DOA) and polarization parameters with coherent signal sources based on an improved block structure of block sparse Bayesian learning (BSBL). The array is a uniform linear dual-polarization array composed of doubly fed orthogonal linearly…
Leonard Bohnenkämper, Luca Parmigiani, Cedric Chauve, Jens Stoye
Genomic rearrangements are major drivers of evolution and genetic disease. However, studying rearrangements requires segmenting the genomes of interest into conserved regions, called synteny blocks, that highlight structural differences between genomes. Synteny blocks are typically defined from annotated genes or…
Ruoqi Zhao, Christian Hettich, Jun Zhang, Meiyi Liu + 1 more
A multistate energy decomposition analysis (MS-EDA) method is introduced for excimers using density functional theory. Although EDA has been widely applied to intermolecular interactions in the ground-state, few methods are currently available for excited state complexes. Here, the total energy of an excimer state is…
Mehmet Aziz Yirik, Maria Sorokina, Christoph Steinbeck
The generation of constitutional isomer chemical spaces has been a subject of cheminformatics since the early 1960s, with applications in structure elucidation and elsewhere. In order to perform such a generation efficiently, exhaustively and isomorphism-free, the structure generator needs to ensure the building of…
Xinyao Li, Akhilesh Tyagi, Loris Nanni
Over the last ten years, there has been a significant interest in employing nonnegative matrix factorization (NMF) to reduce dimensionality to enable a more efficient clustering analysis in machine learning. This technique has been applied in various image processing applications within the fields of computer vision…
Pratyusha Chowdari Ch, J.B. Seventline
Background: This paper presents an efficient two-dimensional (2-D) finite impulse response (FIR) filter using block processing for two different symmetries. Architectures for a general filter (without symmetry) and two symmetrical filters (diagonal and quadrantal symmetry) are implemented. The proposed architectures…
Pablo Soto-Quiros
This paper presents a parallel implementation of a kind of discrete Fourier transform (DFT): the vector-valued DFT. The vector-valued DFT is a novel tool to analyze the spectra of vector-valued discrete-time signals. This parallel implementation is developed in terms of a mathematical framework with a set of block…
Charles Eads
This report describes and illustrates a set of automatable multicomponent exponential relaxation analysis protocols that are model-agnostic and suited to extracting information under circumstances when little prior knowledge about the underlying system is used. Methods are illustrated and mathematical and physical…
Sudesh K. Srivastav, Apurv Srivastav
We study balanced n-ary block designs that allow repeated treatments within blocks, motivated by applications in dose-response and repeated-measure experiments. We introduce a master (k + 1)-ary design with explicit replication and pairwise concurrence parameters. Systematic symmetry-preserving deletions generate…