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Titlebook: AI 2013: Advances in Artificial Intelligence; 26th Australian Join Stephen Cranefield,Abhaya Nayak Conference proceedings 2013 Springer Int

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31#
發(fā)表于 2025-3-26 22:36:13 | 只看該作者
32#
發(fā)表于 2025-3-27 04:04:18 | 只看該作者
0302-9743 and optimisation; evolutionary computation; game playing; knowledge representation and reasoning; machine learning and data mining; natural language processing and information retrieval; planning and scheduling.978-3-319-03679-3978-3-319-03680-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
33#
發(fā)表于 2025-3-27 08:05:23 | 只看該作者
34#
發(fā)表于 2025-3-27 12:15:27 | 只看該作者
Applied Cognitive Science and Technologysponse to stimuli. The results provide preliminary evidence for consistency of PNG activation in response to known stimuli, although these results are limited by problems with the current methods for detecting PNG activation.
35#
發(fā)表于 2025-3-27 16:21:17 | 只看該作者
Rituparna Chaki,Khalid Saeed,Nabendu Chaki sparse loadings via ..-norm. Experiment on Pitprop data illustrates the row-sparsity of this modified regression model for PCA and experiment on YaleB face database demonstrates the effectiveness of this model for PCA in graph embedding.
36#
發(fā)表于 2025-3-27 21:04:07 | 只看該作者
37#
發(fā)表于 2025-3-27 22:33:48 | 只看該作者
John S. Markowitz PharmD,Guo Yu PhDrties. In addition, we prove that the solution also satisfies the most fundamental game theoretic properties such as symmetry and Pareto optimality. Finally, we discuss the relationship between merging operators and bargaining solutions under integrity constraints.
38#
發(fā)表于 2025-3-28 06:02:05 | 只看該作者
Swagata Saha Sau,Rajat Kumar Palg, our sparse-grid variant is therefore able to segment larger images. We evaluate the method on real-world images from the Berkeley Segmentation Dataset. The results indicate that images with 150,000 pixels can be segmented by solving an eigenvalue system of dimensions 500 × 500 instead of 150, 000 × 150, 000.
39#
發(fā)表于 2025-3-28 06:48:43 | 只看該作者
40#
發(fā)表于 2025-3-28 13:03:40 | 只看該作者
https://doi.org/10.1007/978-3-319-03680-9evolutionary algorithm; image analysis; optimization problem; recommender systems; social network analys
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