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Titlebook: Machine Learning, Optimization, and Big Data; First International Panos Pardalos,Mario Pavone,Vincenzo Cutello Conference proceedings 2015

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31#
發(fā)表于 2025-3-27 00:21:43 | 只看該作者
32#
發(fā)表于 2025-3-27 04:13:48 | 只看該作者
Effect of the Dynamic Topology on the Performance of PSO-2S Algorithm for Continuous Optimization,the performance of PSO-2S, this paper proposes a novel variant of this algorithm, called DPSO-2S, which uses the Dcluster neighborhood topologies to organize the communication networks between the particles. Experiments were conducted on a set of classical benchmark functions. The obtained results p
33#
發(fā)表于 2025-3-27 07:20:32 | 只看該作者
Heuristic for Site-Dependent Truck and Trailer Routing Problem with Soft and Hard Time Windows and plit deliveries. In the considered problem a truck can leave its trailer for unloading or parking, make a truck-subtour to serve truck-customers, and return back to take the trailer. This can be done several times in one route. In our heuristic every route is constructed by sequentially inserting cu
34#
發(fā)表于 2025-3-27 12:57:18 | 只看該作者
35#
發(fā)表于 2025-3-27 16:42:54 | 只看該作者
36#
發(fā)表于 2025-3-27 21:19:36 | 只看該作者
Alternating Direction Method of Multipliers for Regularized Multiclass Support Vector Machines,iclass SVM (MSVM) which are more complex problems. Initially, MSVMs were solved by considering their dual formulations which are quadratic programs and can be solved by standard second-order methods. However, the duals of MSVMs with regularizers are usually more difficult to formulate and computatio
37#
發(fā)表于 2025-3-28 00:32:59 | 只看該作者
Tree-Based Response Surface Analysis, one single computer-simulated experiment can still take a significant amount of time. Hence, in order to minimize the amount of simulations needed to investigate a certain design space, different approaches within the design of experiments area are used. One of the used approaches is to minimize th
38#
發(fā)表于 2025-3-28 04:12:31 | 只看該作者
39#
發(fā)表于 2025-3-28 08:41:18 | 只看該作者
40#
發(fā)表于 2025-3-28 12:16:47 | 只看該作者
Intent Recognition in a Simulated Maritime Multi-agent Domain,ethod for recognizing intentions in highly populated multi-agent environments. Low-level intentions, representing basic activities, are detected through a novel formulation of Hidden Markov Models with perspective-taking capabilities. Higher level intentions, involving multiple agents, are detected
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