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A branch-and-bound algorithm for the quadratic assignment problem based on the Hungarian method

Peter Hahn, Thomas Grant, Nat Hall
1998 European Journal of Operational Research  
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

Stefano Quer, Andrea Marcelli, Giovanni Squillero
2020 Computation  
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]

M. Fornasier
2009 Lecture Notes in Computer Science  
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

H. Chau Nguyen, Riccardo Zecchina, Johannes Berg
2017 Advances in Physics  
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

Ben-Bright Benuwa, Yongzhao Zhan, Benjamin Ghansah, Ernest K. Ansah, Andriana Sarkodie
2018 Mathematical Problems in Engineering  
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

Rosa M.V. Figueiredo, Martine Labbé, Cid C. de Souza
2011 Computers & Operations Research  
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]

Ziheng Chen, Xiao-Jun Wu, Tianyang Xu, Rui Wang, Zhiwu Huang, Josef Kittler
2022 arXiv   pre-print
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

Carla Michini
2012 4OR  
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

J. Kurzak, P. Luszczek, M. Faverge, J. Dongarra
2013 IEEE Transactions on Parallel and Distributed Systems  
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

Fengzhi Guo, Shijie Zhang, Tingting Zhang, Anhui Zhang, Chih-Chiang Chen
2021 Mathematical Problems in Engineering  
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

Tingxing Dong, Azzam Haidar, Stanimire Tomov, Jack Dongarra
2017 Procedia Computer Science  
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

Zhouzhou He, Xi Li, Zhongfei Zhang, Fei Wu, Xin Geng, Yaqing Zhang, Ming-Hsuan Yang, Yueting Zhuang
2017 IEEE Transactions on Image Processing  
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]

Antonio Vergari, Nicola Di Mauro, Floriana Esposito
2015 Lecture Notes in Computer Science  
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

Miguel A. Gonzalez-Mesa, Eladio D. Gutierrez, Oscar Plata
2013 Procedia Computer Science  
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

Marc Baboulin, Jack Dongarra, Adrien Rémy, Stanimire Tomov, Ichitaro Yamazaki
2017 Concurrency and Computation  
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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