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Siavash Haghiri
Siavash Haghiri
Research scientist at Zalando
Verified email at informatik.uni-tuebingen.de - Homepage
Title
Cited by
Cited by
Year
Comparison-based nearest neighbor search
S Haghiri, D Ghoshdastidar, U von Luxburg
Artificial Intelligence and Statistics, 851-859, 2017
442017
Comparison-based random forests
S Haghiri, D Garreau, U Luxburg
International Conference on Machine Learning, 1871-1880, 2018
382018
Active one-class learning by kernel density estimation
A Ghasemi, MT Manzuri, HR Rabiee, MH Rohban, S Haghiri
2011 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2011
172011
Estimation of perceptual scales using ordinal embedding
S Haghiri, FA Wichmann, U von Luxburg
Journal of vision 20 (9), 14-14, 2020
162020
Insights into ordinal embedding algorithms: A systematic evaluation
LC Vankadara, S Haghiri, M Lohaus, FU Wahab, U von Luxburg
arXiv preprint arXiv:1912.01666, 2019
14*2019
Comparison-based framework for psychophysics: Lab versus crowdsourcing
S Haghiri, P Rubisch, R Geirhos, F Wichmann, U von Luxburg
arXiv preprint arXiv:1905.07234, 2019
102019
Locality preserving discriminative dictionary learning
S Haghiri, HR Rabiee, A Soltani-Farani, SA Hosseini, M Shadloo
2014 IEEE International Conference on Image Processing (ICIP), 5242-5246, 2014
102014
Efficient small-world and scale-free functional brain networks at rest using k-nearest neighbors thresholding
CG Forlim, S Haghiri, S Düzel, S Kühn
bioRxiv, 628453, 2019
32019
Exploiting structural information of data in active learning
M Shadloo, H Beigy, S Haghiri
Artificial Intelligence and Soft Computing: 13th International Conference …, 2014
22014
Comparison-based methods in machine learning
S Haghiri
Universität Tübingen, 2021
12021
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation
U von Luxburg, FU Wahab, M Lohaus, S Haghiri, LC Vankadara
arXiv, 2021
2021
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation
L Chennuru Vankadara, S Haghiri, M Lohaus, FU Wahab, U von Luxburg
arXiv e-prints, arXiv: 1912.01666, 2019
2019
Supplementary material for the article: Comparison-Based Random Forests
S Haghiri, D Garreau, U von Luxburg
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Articles 1–13