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M. Ehsan Abbasnejad I am a Senior Research Fellow at the Australian Institute for Machine Learning (AIML). Previously, I was a PhD student at the Australian National University (ANU) and a Graduate Researcher in the Machine Learning Group at the National ICT Australia (NICTA). I work closely with Assoc. Prof. Javen Shi and Prof. Anton van den Hengel. I was supervised by Prof. Scott Sanner for my PhD. Email: ehsan (dot) abbasnejad (at) adelaide (dot) edu (dot) au |
News:
We have an opening for a new PhD position to be co-supervised between University of Adelaide and the IMT-Atlantique in France. (September, 2019) [details]
Won 2nd Prize of OZ Minerals Explorer Challenge as a member of DeepSightX team. (June, 2019) [News details] [Media]
Selected Publications:
A Generative Adversarial Density Estimator [Oral]
E. Abbasnejad, Q. Shi, A. van den Hengel, L. Liu,
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. Long Beach, CA, USA.
[Link]
What's to Know? Uncertainty as a Guide to Asking Goal-Oriented Questions
E. Abbasnejad, Q. Wu, Q. Shi, A. van den Hengel,
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. Long Beach, CA, USA.
[Link]
Active Learning from Noisy Tagged Images
E. Abbasnejad, A. Dick, Q. Shi, A. van den Hengel,
In Proceedings of British Machine Vision Conference, 2018 (CVPR), 2018. Newcastle, UK.
[Link]
3D Hand Pose Estimation using Simulation and Partial-Supervision with a Shared Latent Space [Oral]
M. Abdi, E. Abbasnejad, C. P. Lim, S. Nahavandi,
In Proceedings of British Machine Vision Conference, 2018 (CVPR), 2018. Newcastle, UK.
[Link]
Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables
A. Abedin, E. Abbasnejad, Q. Shi, D. Ranasinghe, H. Rezatofighi,
In Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems (MobiQuitous), 2018. New York, NY, USA.
[Link]
Infinite Variational Autoencoder for Semi-Supervised Learning
E. Abbasnejad, A. Dick, A. van den Hengel,
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. Honolulu, USA.
[link] [supplement]
Label Filters for Large Scale Multilabel Classification
A. Niculescu-Mizil, E. Abbasnejad,
In Proceedings of The 20th International Conference on Artificial Intelligence and Statistics, 2017, Fort Lauderdale, USA
[Link]
DeepSetNet: Predicting Sets with Deep Neural Networks
H. Rezatofighi, V. Kumar, A. Milan, E. Abbasnejad, A. Dick, I. Reid,
The IEEE International Conference on Computer Vision (ICCV), 2017. Venice, Italy.
[link]
Distribution Based Workload Modelling of Continuous Queries in Clouds
A. Khoshkbarforoushha, R. Ranjan, R. Gaire, E. Abbasnejad, L. Wang, A. Zomaya,
In IEEE Transactions on Emerging Topics in Computing, 2016.
[link]
Loss-calibrated Monte Carlo Action Selection
E. Abbasnejad, J. Domke, S. Sanner,
In Proceedings of the 26th Conference on Artificial Intelligence (AAAI), 2015. Austin, USA.
[link] [supplement] [code]
Linear-time Gibbs Sampling in Piecewise Graphical Models
H. Afshar, S. Sanner, E. Abbasnejad,
In Proceedings of the 26th Conference on Artificial Intelligence (AAAI), 2015. Austin, USA.
Decision-theoretic Sparsification for Gaussian Process Preference Learning
E. Abbasnejad, E. V. Bonilla, S. Sanner,
Proceedings of the Machine Learning and Knowledge Discovery in Databases - European Conference (ECML PKDD). Prague, Czech Republic, 2013.
[link]
[dataset]
[code]
Learning Community-based Preferences via Dirichlet Process Mixtures of Gaussian Processes
E. Abbasnejad, S. Sanner, E. V. Bonilla, P. Poupart,
In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013. Beijing, China.
[link] [dataset] [supplement] [code]
Symbolic Variable Elimination for Discrete and Continuous Graphical Models
S. Sanner, E. Abbasnejad,
In Proceedings of the 26th Conference on Artificial Intelligence (AAAI), 2012. Toronto, Canada.
[link]
New Objectives for Social Collaborative Filtering
J. Noel, S. Sanner, K.-N. Tran, P. Christen, L. Xie, E. Bonilla, E. Abbasnejad, N. Della Penna, In Proceedings of the 21st International Conference on the World Wide Web (WWW), 2012. Lyon, France. [link]
A Survey of The State of the Art in Learning the Kernels
E. Abbasnejad, Ramachandram D., Mandava R. Journal of Neural Computing and Applications, 2011 [link]
The Common Solution of the Pair of Fuzzy Matrix Equations
Amir Sadeghia, Saeid Abbasbandy, E. AbbasnejadWorld Applied Science Journal, 2011 [link]
On Solving Systems of Fuzzy Matrix Equation
Amir Sadeghia, E. Abbasnejad, Ahmad Izani Md. Ismail Far East Journal of Applied Mathematics, 2011 [link]
An Unsupervised Approach to Learn the Kernel Functions: From Global Influence to Local Similarity
E. Abbasnejad, Ramachandram D., Mandava R. Journal of Neural Computing and Applications, 2010 [link]
Optimizing Kernel Functions using Transfer Learning from Unlabeled Data
E. Abbasnejad, Ramachandram D., Mandava R. International Conference on Machine Vision, 2009 [link]
Job Experience:
Thesis:
Scalable Loss-calibrated Bayesian Decision Theory and Preference Learning
E. Abbasnejad, PhD Thesis, Australian National University [link]
Learning and Optimization of Kernel Functions from Insufficiently Labeled Examples
E. Abbasnejad, MSc Thesis, Universiti Sains Malaysia
