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A branch-and-bound algorithm for the quadratic assignment problem based on the Hungarian method
1998
European Journal of Operational Research
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The algorithm is based on a Dual Procedure (DP) similar to the Hungarian method for solving the Linear Assignment Problem. ...
The DP, however, does not guarantee a solution. It is used in our algorithm to calculate lower bounds on solutions to the QAP. ...
identical amount, thus preserving their order with respect to cost. ...
doi:10.1016/s0377-2217(97)00063-5
fatcat:ia6tuxfilrgxpgwhezldxukxnq
The Maximum Common Subgraph Problem: A Parallel and Multi-Engine Approach
2020
Computation
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Finally, we propose a portfolio approach, which integrates all the different local search algorithms as component tools; such portfolio, rather than choosing the best tool for a given instance up-front ...
We analyze a parallel multi-core implementation that exploits a divide-and-conquer approach based on a thread pool, which does not deteriorate the original algorithmic efficiency and it minimizes data ...
Acknowledgments: The author wish to thank Gabriele Mosca for implementing the first version of the tools and performing the initial experimental evaluation. ...
doi:10.3390/computation8020048
fatcat:akhvyp47mvfj3abu5qtismm67i
Compressive Algorithms—Adaptive Solutions of PDEs and Variational Problems
[chapter]
2009
Lecture Notes in Computer Science
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large scale problems. ...
The introduction of this paper presents an historical excursus on the developments of the main ideas behind compressive algorithms and stresses the common features of diverse applications. ...
Acknowledgment The author acknowledges the support of the FWF project no. Y-432-N15 STARTaward "Sparse Approximation and Optimization in High Dimensions". ...
doi:10.1007/978-3-642-03596-8_9
fatcat:ypq5fqzcajc5pma5vw56mc3fwm
Inverse statistical problems: from the inverse Ising problem to data science
2017
Advances in Physics
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In inverse problems, the usual procedure of statistical physics needs to be reversed: Instead of calculating observables on the basis of model parameters, we seek to infer parameters of a model based on ...
We also review the inverse Ising problem in the non-equilibrium case, where the model parameters must be reconstructed based on non-equilibrium statistics. ...
Many methods for feature selection are available from statistics [93] , however there is no consensus on the best method for the inverse Ising problem. ...
doi:10.1080/00018732.2017.1341604
fatcat:yof3mukd6ng2rizgbvuwzckdz4
Sparsity Based Locality-Sensitive Discriminative Dictionary Learning for Video Semantic Analysis
2018
Mathematical Problems in Engineering
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In the proposed algorithm, a discriminant loss function for the category based on sparse coding of the sparse coefficients is introduced into structure of locality-sensitive dictionary learning (LSDL) ...
Based on the issues stated afore, a novel learning algorithm, called sparsity based locality-sensitive discriminative dictionary learning (SLSDDL) for VSA is proposed in this paper. ...
proposed method is best among all the comparative approaches on most categories. ...
doi:10.1155/2018/9312563
fatcat:qnrsbiwnxjdffcj3g5kkcvpxhe
An exact approach to the problem of extracting an embedded network matrix
2011
Computers & Operations Research
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We study the problem of detecting a maximum embedded network submatrix in a { À 1,0,+ 1}-matrix. Our aim is to solve the problem to optimality. ...
We introduce a 0-1 integer linear programming formulation for this problem based on its representation over a signed graph. ...
In order to better measure the effectiveness of our exact approach, we also provide numerical results for a set of random instances of the DMERN problem. ...
doi:10.1016/j.cor.2011.01.003
fatcat:xhkpe65jebefvew6ic6dtrm6i4
MSNet: A Deep Multi-scale Submanifold Network for Visual Classification
[article]
2022
arXiv
pre-print
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Although there are many different attempts to develop effective deep architectures for data processing on the Riemannian manifold of SPD matrices, a very few solutions explicitly mine the local geometrical ...
Based on this analysis, we postulate a submanifold selection principle to guide the design of our MSNet. ...
RELATED WORK In order to take advantage of deep learning techniques, some effort has been made to generalize the Euclidean deep learning into a Riemannian one. ...
arXiv:2201.10145v2
fatcat:pvgkpoatbrburdeqdzqb4nfoty
The stable set problem: some structural properties and relaxations
2012
4OR
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In this chapter we present a concave reformulation for set covering problems, where integrality constraints are dropped and the original linear objective function is replaced by a concave one, penalizing ...
For a review of the state of the art heuristics for mixed integer and binary programs we recommend [2] and [19] . ...
The best known algorithm for linear programming, the simplex method was defined by Dantzig in 1951 and is still one of the most efficient methods to solve LP problems. ...
doi:10.1007/s10288-012-0218-8
fatcat:fvnfrmlqtrcqliq5owka6tdl7m
LU Factorization with Partial Pivoting for a Multicore System with Accelerators
2013
IEEE Transactions on Parallel and Distributed Systems
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Performance in excess of one TeraFLOPS is achieved using four AMD Magny Cours CPUs and four NVIDIA Fermi GPUs. ...
LU factorization with partial pivoting is a canonical numerical procedure and the main component of the high performance LINPACK benchmark. ...
ACKNOWLEDGMENTS The authors thank David Luebke, Steven Parker, and Massimiliano Fatica for their insightful comments about the Fermi architecture. ...
doi:10.1109/tpds.2012.242
fatcat:6dljefl6ozcohczcs4qhtiwlbi
Event-Triggered Adaptive Sliding Mode Attitude Containment Control for Microsatellite Cluster under Directed Graph
2021
Mathematical Problems in Engineering
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In order to investigate the attitude containment control problem for a microsatellite cluster, an event-triggered adaptive sliding mode attitude containment control algorithm is proposed for the satellite ...
At first, the event-triggered control strategy is introduced into the attitude containment control problem for the microsatellite cluster. ...
Efforts to overcome these problems have led to the proposal of event-triggered control strategy. ...
doi:10.1155/2021/6652342
fatcat:nr5sjm47dfay3py3pksyzunj6q
Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices
2017
Procedia Computer Science
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We illustrated our batched BLAS approach to optimize batched bi-diagonalization progressively on a K40c GPU. ...
A challenging class of problems arising in many GPU applications, called batched problems, involves linear algebra operations on many small-sized matrices. ...
The methods in this paper can be applied to other two-sided factorizations, e.g., the Hessenberg reduction (GEHRD) and the tri-diagonalization (SYTRD), as well. ...
doi:10.1016/j.procs.2017.05.237
fatcat:4rlcq3vipzde3dnesgusd6j6vy
Data-Dependent Label Distribution Learning for Age Estimation
2017
IEEE Transactions on Image Processing
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Without any prior assumptions on the forms of label distribution learning, our approach is able to flexibly model the sample-specific context aware label distribution properties by solving a multi-task ...
The proposed approach is capable of effectively discovering the intrinsic age distribution patterns for cross-age correlation analysis on the basis of the local context structures of face samples. ...
In the related field, many efforts of face identification design various deep neural networks to extract face features. ...
doi:10.1109/tip.2017.2655445
pmid:28103557
fatcat:hhpaw3worbhdbeenrbwene3ohm
Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning
[chapter]
2015
Lecture Notes in Computer Science
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Here, we enhance one of the best structure learner, LearnSPN, aiming to improve both the structural quality of the learned networks and their achieved likelihoods. ...
We prove our claims by empirically evaluating the learned SPNs on several benchmark datasets against other competitive SPN and PGM structure learners. ...
One way to control the number of edges is to layer the nodes into a deep architecture, where parameters are reused across the levels. ...
doi:10.1007/978-3-319-23525-7_21
fatcat:gz3ctb24gff23kcz34qi3t4jy4
Parallelizing the Sparse Matrix Transposition: Reducing the Programmer Effort Using Transactional Memory
2013
Procedia Computer Science
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This manager is in charge of ordering transaction commits when required in order to preserve data dependencies. ...
This work discusses the parallelization of an irregular scientific code, the transposition of a sparse matrix, comparing two multithreaded strategies on a multicore platform: a programmer-optimized parallelization ...
Note that the programmer effort to develop this version is much lower than in the previous data-parallel code, and with no deep knowledge about the application. ...
doi:10.1016/j.procs.2013.05.214
fatcat:tohie4buerhmjp2zmnivfjlsxi
Solving dense symmetric indefinite systems using GPUs
2017
Concurrency and Computation
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the matrix entirely on the GPU or in a communication-avoiding fashion). ...
This paper studies the performance of different algorithms for solving a dense symmetric indefinite linear system of equations on multicore CPUs with a Graphics Processing Unit (GPU). ...
Acknowledgments The authors would like to thank the NSF (grant #ACI-1339822), NVIDIA, and MathWorks for supporting this research effort. ...
doi:10.1002/cpe.4055
fatcat:v36zyi35qrb7zpzw4tuyzfy53a
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