Advanced Intelligent Computing Theories and Applications: by De-Shuang Huang, Kyungsook Han

By De-Shuang Huang, Kyungsook Han

This booklet - along with the double quantity LNCS 9225-9226 - constitutes the refereed court cases of the eleventh overseas convention on clever Computing, ICIC 2015, held in Fuzhou, China, in August 2015.

The eighty four papers of this quantity have been rigorously reviewed and chosen from 671 submissions. unique contributions concerning this subject have been specially solicited, together with theories, methodologies, and purposes in technology and expertise. This yr, the convention targeted in general on computer studying idea and techniques, tender computing, photo processing and machine imaginative and prescient, wisdom discovery and information mining, ordinary language processing and computational linguistics, clever regulate and automation, clever conversation networks and internet functions, bioinformatics thought and techniques, healthcare and scientific tools, and knowledge security.

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Additional resources for Advanced Intelligent Computing Theories and Applications: 11th International Conference, ICIC 2015, Fuzhou, China, August 20-23, 2015. Proceedings, Part III

Example text

From Table 3, we can observe that on the kin40 k dataset, our proposed algorithm is more precise than the other algorithms due to fewer approximations. A possible reason why our algorithm consumes so much time is that on a real dataset that doesn’t come from a GP or MGP model, our algorithm needs much more iterations. Therefore, a further improvement can be made by preprocessing a real dataset so that it is more like a dataset simulated from a MGP. Linear regression is still rather coarse since the kin40k dataset is highly non-linear [34].

In: Advances in Neural Information Processing Systems, vol. 18 (2005) 36. : Sparse greedy Gaussian process regression. Adv. Neural Inf. Process. Syst. 13, 619–625 (2000) 37. : Machine Learning: A Probabilistic Perspective. MIT Press, Cambridge (2012) 38. : A tutorial on support vector regression. Stat. Comput. com Abstract. In this paper, through polar coordinates and constructing an auxiliary function we prove the maximum principle in the unbounded domain X as following: suppose that there exists uðnÞ 2 CðXÞ bounded above, solution of & LuðnÞ þ cðnÞuðnÞ !

Diff. Equ. 119, 450–472 (1995) 2. : Monotonicity for elliptic equations in unbounded domains. Commun. Pure Appl. Math. 50, 1088–1111 (1997) 3. : One dimensional symmetry in the heisenberg group. Annali della Scuola Normale Superiore di Pisa 3, 1–17 (2001) 4. : Fundamental solutions for a class of hypoelliptic PDE generated by composition of quadratic forms. Trans. Am. Math. Soc. 258, 147–153 (1980) 5. : Regularity near the characteristic set in the nonlinear dirichlet problem and conformal geometry of sub-laplacians.

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