Ehsan Abbasnejad
Ehsan Abbasnejad
Australian Institute for Machine Learning, University of Adelaide
Verified email at - Homepage
Cited by
Cited by
Infinite Variational Autoencoder for Semi-Supervised Learning
E Abbasnejad, A Dick, A van den Hengel
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu …, 2017
New objective functions for social collaborative filtering
J Noel, S Sanner, KN Tran, P Christen, L Xie, EV Bonilla, E Abbasnejad, ...
Proceedings of the 21st international conference on World Wide Web, 859-868, 2012
A survey of the state of the art in learning the kernels
ME Abbasnejad, D Ramachandram, R Mandava
Knowledge and information systems 31 (2), 193-221, 2012
Low-rank linear cold-start recommendation from social data
S Sedhain, A Menon, S Sanner, L Xie, D Braziunas
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
The common solution of the pair of fuzzy matrix equations
A Sadeghi, S Abbasbandy, ME Abbasnejad
World Applied Sciences 15 (2), 232-238, 2011
Symbolic variable elimination for discrete and continuous graphical models
S Sanner, E Abbasnejad
Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 2012
On solving systems of fuzzy matrix equation
A Sadeghi, ME Abbasnejad, MI Ahmad
Far East Journal of Applied Mathematics 59 (1), 31-44, 2011
Deepsetnet: Predicting sets with deep neural networks
SH Rezatofighi, VK BG, A Milan, E Abbasnejad, A Dick, I Reid
2017 IEEE International Conference on Computer Vision (ICCV), 5257-5266, 2017
Distribution based workload modelling of continuous queries in clouds
A Khoshkbarforoushha, R Ranjan, R Gaire, E Abbasnejad, L Wang, ...
IEEE Transactions on Emerging Topics in Computing 5 (1), 120-133, 2016
Learning community-based preferences via dirichlet process mixtures of gaussian processes
E Abbasnejad, S Sanner, EV Bonilla, P Poupart
Twenty-third international joint conference on artificial intelligence, 2013
A note on solving the fuzzy Sylvester matrix equation, journal of computational analysis and applications
A Sadeghi, MI Ahmad, A Ahmad, ME Abbasnejad
Reflection, Refraction, and Hamiltonian Monte Carlo.
HM Afshar, J Domke
NIPS, 3007-3015, 2015
Symbolic dynamic programming for continuous state and action mdps
Z Zamani, S Sanner, C Fang
Proceedings of the AAAI Conference on Artificial Intelligence 26 (1), 2012
Joint probabilistic matching using m-best solutions
S Hamid Rezatofighi, A Milan, Z Zhang, Q Shi, A Dick, I Reid
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Invisible backdoor attacks against deep neural networks
S Li, BZH Zhao, J Yu, M Xue, D Kaafar, H Zhu
arXiv preprint arXiv:1909.02742, 2019
Februus: Input purification defense against trojan attacks on deep neural network systems
BG Doan, E Abbasnejad, DC Ranasinghe
Annual Computer Security Applications Conference, 897-912, 2020
Reinforcement learning with attention that works: A self-supervised approach
A Manchin, E Abbasnejad, A van den Hengel
International Conference on Neural Information Processing, 223-230, 2019
Resource usage estimation of data stream processing workloads in datacenter clouds
A Khoshkbarforoushha, R Ranjan, R Gaire, PP Jayaraman, J Hosking, ...
arXiv preprint arXiv:1501.07020, 2015
Soccer event detection via collaborative multimodal feature analysis and candidate ranking.
AA Halin, M Rajeswari, M Abbasnejad
Int. Arab J. Inf. Technol. 10 (5), 493-502, 2013
Cluster sparsity field for hyperspectral imagery denoising
L Zhang, W Wei, Y Zhang, C Shen, A Van Den Hengel, Q Shi
European conference on computer vision, 631-647, 2016
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