Chalmers University of Technology University of Gothenburg Gothenburg,Sweden2019. Supervisor: Morteza Haghir Chehreghani, Department of Computer Science and

Mostafa Haghir Chehreghani, Morteza Haghir Chehreghani, Caro Lucas, Masoud Rahgozar: OInduced: An Efficient Algorithm for Mining Induced Patterns From Rooted Ordered Trees. IEEE Trans. Syst. Man Cybern. Part A 41 (5): 1013-1025 (2011)

Recently, the use of this distance measure is shown to improve the K-nearest neighbor classiﬁcation results. We consider the computational aspects of this problem and propose 12/21/2018 ∙ by Morteza Haghir Chehreghani, et al. ∙ Chalmers University of Technology ∙ 0 ∙ share We study nonparametric feature extraction from hierarchies. The commonly used Minimax distance measures correspond to building a dendrogram with single linkage criterion, with the definition of specific forms of a level function and a distance function over that.

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Chalmers University of Technology Examiner: Morteza Haghir Chehreghani, Department of Computer Science and Engineering Master’sThesis2020

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Chalmers offers a cultivating and inspiring working environment in the dynamic city of Gothenburg. Read more about working at Chalmers and our benefits for employees. Application procedure Read more at Chalmers webpage. Application deadline: 5th of November - 2020. For questions, please contact: Associate professor, Morteza Haghir Chehreghani

claim profile ∙ 0 followers Chalmers University of Technology Research Scientist at Xerox Research Center Europe ( NAVER Mostafa Haghir Chehreghani, Morteza Haghir Chehreghani, Caro Lucas, Masoud Rahgozar: OInduced: An Efficient Algorithm for Mining Induced Patterns From Rooted Ordered Trees. IEEE Trans.

Follow. Euhanna Ghadimi. Ericsson AB, Sweden. Verified email at Morteza Haghir Chehreghani Abstract We study Minimax distance measures for K-nearest neighbor search and classiﬁcation.
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Se Morteza Haghir Chehreghanis profil på LinkedIn, världens största yrkesnätverk. Morteza har Associate Professor at Chalmers University of Technology. Chalmers University of TechnologyChalmers tekniska högskola / Chalmers University of Technology.

Newsletter. Welcome to Chalmers AI Research Center, CHAIR Spotlight on Research. In this series of AI short talks Morteza Haghir Chehreghani Associate Professor at Data Science and AI division, Department of Computer Science and Engineering at Chalmers, will handle the … Morteza Haghir Chehreghani is Associate Professor of AI and Machine Learning at Chalmers University of Technology, Department of Computer Science and Engineering, Data Science and AI division. He holds a Ph.D.
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Carl Johnell, Morteza Haghir Chehreghani Chalmers University of Technology cjohnell@gmail.com, morteza.chehreghani@chalmers.se Abstract We study Frank-Wolfe algorithms – standard, pairwise, and away-steps – for efﬁcient optimization of Dominant Set Clus-tering. We present a uniﬁed and computationally efﬁcient

18, 2012. PhD Student of Computer Science, Chalmers University of Technology - ‪‪Citerat av 7‬‬ A Rahbar, A Panahi, C Bhattacharyya, D Dubhashi, MH Chehreghani. JM Buhmann, MH Chehreghani, M Frank, AP Streich. Proceedings of ICML Workshop on Unsupervised and Transfer Learning, 51-64, 2012.