M. C. GANİZ, "Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation," IEEE International Conference on Systems, Man, and Cybernetics (SMC) , Budapest, Hungary, pp.2242-2247, 2016
GANİZ, M. C. 2016. Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation. IEEE International Conference on Systems, Man, and Cybernetics (SMC) , (Budapest, Hungary), 2242-2247.
GANİZ, M. C., (2016). Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation . IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp.2242-2247). Budapest, Hungary
GANİZ, MURAT. "Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation," IEEE International Conference on Systems, Man, and Cybernetics (SMC), Budapest, Hungary, 2016
GANİZ, MURAT C. . "Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation." IEEE International Conference on Systems, Man, and Cybernetics (SMC) , Budapest, Hungary, pp.2242-2247, 2016
GANİZ, M. C. (2016) . "Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation." IEEE International Conference on Systems, Man, and Cybernetics (SMC) , Budapest, Hungary, pp.2242-2247.
@conferencepaper{conferencepaper, author={MURAT CAN GANİZ}, title={Semi-Supervised Learning using Higher-Order Co-occurrence Paths to Overcome the Complexity of Data Representation}, congress name={IEEE International Conference on Systems, Man, and Cybernetics (SMC)}, city={Budapest}, country={Hungary}, year={2016}, pages={2242-2247} }