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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

作者： Chan, Hau Loukides, Grigorios Su, Zhenghui Univ Nebraska Lincoln NE 68588 USA Kings Coll London London England

ISBN: (纸本)9783030676643;9783030676636

We study a new optimization problem that minimizes the ratio of two monotone k-submodular functions. The problem has applications in sensor placement, influence maximization, and feature selection among many others where one wishes to make a tradeoff between two objectives, measured as a ratio of two functions (e.g., solution cost vs. quality). We develop three greedy based algorithms for the problem, with approximation ratios that depend on the curvatures and/or the values of the functions. We apply our algorithms to a sensor placement problem where one aims to install k types of sensors, while minimizing the ratio between cost and uncertainty of sensor measurements, as well as to an influence maximization problem where one seeks to advertise k products to minimize the ratio between advertisement cost and expected number of influenced users. Our experimental results demonstrate the effectiveness of minimizing the respective ratios and the runtime efficiency of our algorithms. Finally, we discuss various extensions of our problems.

关键词： k-submodular function greedy algorithm Approximation

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Reaching for upper bound ROUGE score of extractive summarization methods

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PEERJ COMPUTER SCIENCE 2022年 8卷 e1103页

作者： Akhmetov, Iskander Mussabayev, Rustam Gelbukh, Alexander Kazakh British Tech Univ Alma Ata Kazakhstan Inst Informat & Computat Technol Alma Ata Kazakhstan Inst Politecn Nacl Mexico City Mexico

The extractive text summarization (ETS) method for finding the salient information from a text automatically uses the exact sentences from the source text. In this article, we answer the question of what quality of a summary we can achieve with ETS methods? To maximize the ROUGE-1 score, we used five approaches: (1) adapted reduced variable neighborhood search (RVNS), (2) greedy algorithm, (3) VNS initialized by greedy algorithm results, (4) genetic algorithm, and (5) genetic algorithm initialized by the greedy algorithm results. Furthermore, we ran experiments on articles from the arXive dataset. As a result, we found 0.59 and 0.25 scores for ROUGE-1 and ROUGE-2, respectively achievable by the approach, where the genetic algorithm initialized by the greedy algorithm results, which happens to yield the best results out of the tested approaches. Moreover, those scores appear to be higher than scores obtained by the current state-of-the-art text summarization models: the best score in the literature for ROUGE-1 on the same data set is 0.46. Therefore, we have room for the development of ETS methods, which are now undeservedly forgotten.

关键词： Text summarization Genetic algorithm greedy algorithm Variable neighborhood search Rouge

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Aerodynamic Optimization based on a Discrete Adjoint Framework and Radial Basis Function Mesh Deformation in SU2

Aerodynamic Optimization based on a Discrete Adjoint Framewo...

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AIAA Aviation Forum and Exposition

作者： Abergo, Luca Morelli, Myles Guardone, Alberto Politecn Milan Dept Aerosp Sci & Technol Bldg B12Via La Masa 34 I-20156 Milan MI Italy

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

A Radial Basis Function (RBF) mesh deformation is implemented and coupled with the discrete adjoint framework within the open-source toolkit SU2. The RBF allows to handle more complex geometry than the current elastic deformation approach, while enabling large deformations to expand the design space. Data reduction schemes including multilevel greedy algorithms are used to improve the efficiency of RBF mesh deformation on large data sets. Numerical experiments show a significant reduction of memory usage over the linear elasticity analogy both for two-dimensional cases and for large, three-dimensional problems. Additionally, the mesh deformation process is differentiated by Automatic Differentiation within the discrete adjoint approach, resulting in method-dependent surface sensitivity, thus allowing the Sequential Least Squares Programming optimizer to converge to a new local minimum by modifying the geometrical shape towards the final design.

关键词： Linear Elasticity Data Reduction greedy algorithm Elastic Deformation Aerodynamic Coefficients Winglets Poisson's Ratio Computational Fluid Dynamics Shape Optimization Turbulence Models

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The Drone System based on Optimal Combination algorithm

The Drone System based on Optimal Combination Algorithm

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作者： Rui Zheng Jingyuan Wang Min Wei Beijing Normal University

This paper help CFA design a drones use system that determine the number and the location of SSA drones and Radio Repeater drones to facilitate wildfifires *** establish a model to determine the optimal combination of SSA drones and Radio Repeater *** number of Radio Repeater drones needs to be calculated based on the distance from the EOC to the center of the fire *** the number of SSA drones,we consider the factors of capability,safety,topography and so *** the genetic algorithm,we determine the shortest path of each SSA *** data sigmoid normalization and determining the weight through coefficient of variation,we build a comprehensive capability and safety evaluation index to choose the optimal number of SSA ***,we use DUDC Model to determine the location of hovering radio-repeater *** determine the straight line where the Radio Repeater drones are located,and then use the straight line obtained as the abscissa,uniformly determine the coordinate axis direction and use greedy algorithm to solve where should Radio Repeater drones ***,we summarize the model and explain the strengths of the model.

关键词： Optimal Combination Genetic algorithm Coefficient of Variation DUDC Model greedy algorithm

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3D model-based scan planning for space frame structures considering site conditions

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AUTOMATION IN CONSTRUCTION 2022年 140卷 1页

作者： Li, Dongsheng Liu, Jiepeng Zeng, Yan Cheng, Guozhong Dong, Biqin Chen, Y. Frank Shenzhen Univ Coll Civil & Transportat Engn Shenzhen 518060 Guangdong Peoples R China Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China Penn State Univ Dept Civil Engn Middletown PA 17057 USA

The acquisition of point cloud data from a space frame using terrestrial laser scanning is usually affected by many occluding components and site conditions and therefore needs to achieve optimal priori planning, which is handled as the planning for scanning (P4S) problem. This paper describes a three-dimensional model-based P4S approach for space frame structures, where a space modeling solution is employed to simulate the scanning target and environment. The P4S problem modeling is used to define the visibility analysis and constraints. Lastly, a two-phase optimization is proposed to solve the P4S problem and compared with a weighted greedy algorithm. Experiments were conducted on a full-scale space frame to validate the proposed approach.

关键词： Planning for scanning Space frame Terrestrial laser scanning Genetic algorithm greedy algorithm

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The Performance of Different algorithms to Solve Traveling Salesman Problem 2

The Performance of Different Algorithms to Solve Traveling S...

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2nd International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE)

作者： Bi, Hanqing Yang, Zhuoyuan Wang, Mengxi Dalhousie Univ Sch Comp Sci Halifax NS B3H 4R2 Canada Univ Southern Calif Viterbi Sch Engn Los Angeles CA 90007 USA Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China

ISBN: (纸本)9781665427098

Traveling salesman problem, with extensive potential applications in industries of all sorts, has been studied for decades. Although there are massive solutions put forward, the most efficient and exact way has never been widely acknowledged since this problem is typically NP-hard. We selected three types of most commonly used algorithms to solve this problem: greedy algorithm, Ant Colony algorithm and Simulated Annealing algorithm. With data sets given in TSPLIB, we computed and compared these algorithms in both the shortest distance and the time cost. Based on the statistics obtained from experiments, it can be found that greedy algorithm runs the fastest with a sacrifice of accuracy, whereas Simulated Annealing algorithm searches out the shortest path in a relatively small group of cities and Ant Colony algorithm performs even better when the points increase.

关键词： Traveling salesman problem (TSP) greedy algorithm Ant Colony algorithm Simulated Annealing algorithm

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Approximating Maximum Acyclic Matchings by greedy and Local Search Strategies 26th

Approximating Maximum Acyclic Matchings by Greedy and Local ...

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26th International Computing and Combinatorics Conference (COCOON)

作者： Baste, Julien Fuerst, Maximilian Rautenbach, Dieter Ulm Univ Inst Optimizat & Operat Res Ulm Germany

ISBN: (纸本)9783030581503;9783030581497

A matching M in a graph G is acyclic if the subgraph of G induced by the vertices that are incident to an edge in M is a forest. Even restricted to graphs of bounded maximum degree, the maximum acyclic matching problem is hard. We contribute efficient approximation algorithms for this problem, based on greedy and local search strategies, that have performance guarantees involving the maximum degree of the input graphs.

关键词： Acyclic matching Induced matching greedy algorithm Local search

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Exploring the advancements and challenges of automated machine learning

Exploring the advancements and challenges of automated machi...

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作者： Zhengyang Jin Computer Science University of Electronic Science and Technology of ChinaZhongshan Institute

Automl,a rapidly growing field which is aiming to apply the machine to solve problems that human can't easily deal with. This includes tasks such as feature selection,model selection, and hyperparameter tuning. One of the many advantages about Auto Ml is that it can greatly shorten the cost of researchs and resources cost by applying machine learning to a problem. This makes it accessible to a wider range of users, including those without a background in computer science or *** spite of some advantages of AutoML,many challenges are waiting to be addressed. The main challenge is that it is often challenging to ensure that the models generated by AutoML are of high quality and generalize well to new data. Another challenge is that AutoML can be computationally expensive, which can make it infeasible for some problems. Overall, AutoML has the potential to revolutionize the way we apply machine learning to real-world problems, but it is important to be aware of its limitations and challenges.

关键词： feature selection feature construction model selection hyperparameter tuning ensemble learning greedy algorithm random search grid search organic search model fusion

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The Grapevine Web: Analysing the Spread of False Information in Social Networks with Corrupted Sources 23

The Grapevine Web: Analysing the Spread of False Information...

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Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems

作者： Jacques Bara Charlie Pilgrim Paolo Turrini Stanislav Zhydkov University of Warwick Coventry United Kingdom

ISBN: (纸本)9781450394321

We study the problem of noisy information propagation in networks, where a small number of sources send messages across the network and agents use Bayesian updates to make inferences about the state of the world from the received messages. We provide upper bounds on the total number of sources necessary for learning on a given network and refine the bound in the case of small-world networks. We then extend the model to include an adversarial attacker, who can corrupt some of the information sources. We find that there is an optimal greedy attacking strategy in the case of a single learner, while the multi-learner case is not always solved optimally using greedy approaches. However, despite the influence function not being submodular, we show that the greedy algorithm performs well in practice. We also show that much simpler heuristics, which only look at centrality measures, can also provide a good basis to calculate successful attacking strategies. Finally we analyse the loss of optimality in the case when the attacker has incomplete information about the network and has to estimate the influence of source corruption heuristically. We use real-world social networks, as well as random network models, to empirically evaluate the effectiveness of attacking strategies and suggest a variety of measures to counteract them.

关键词： social networks misinformation centrality measures heuristics greedy algorithm

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Performance analysis of beamforming algorithm based on compressed sensing

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APPLIED ACOUSTICS 2022年 198卷

作者： Sun, Jian Li, Pengyang Mao, Jin Yang, Mingshun Shao, Ding Chen, Yunshuai Li, Jian Wang, Kai Xian Univ Technol Sch Mech & Precis Instrument Engn Xian 710048 Peoples R China Qinchuan Grp Xian Technol Res Inst Co Ltd Xian 710018 Peoples R China

The beamforming (BF) algorithm is widely used in sound source recognition due to its superior perfor-mance, but its main lobe is wide, side lobes are high, and its running speed is slow. Therefore, a method based on the compressed sensing beamforming method is proposed. The sound source measurement model is established, the compressed sensing reconstruction matrix is applied to the beamforming method, and propose a compressed sensing beamforming sound source recognition method. The sound source recognition performance of orthogonal matching pursuit (OMP), generalized orthogonal matching pursuit (gOMP), and regularized orthogonal matching pursuit (ROMP) is compared and analyzed through MATLAB simulation, and the OMP algorithm is selected to combine with the beamforming method. Further study the OMP-BF way and compare and analyze the recognition accuracy and running time of OMP-BF with functional beamforming (F-BF) and L1 minimum norm method beamforming (L1-BF). The results show that the OMP-BF method can accurately identify the sound source location, and the run-ning time is much lower than L1-BF and F-BF. Finally, through experiments, the effectiveness of the algo-rithm is verified. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Beamforming Compressed sensing Sound source recognition greedy algorithm Orthogonal matching tracking

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