Welkom...

Z. Atashgahi MSc (Zahra)

Promovendus

Expertises

Engineering & Materials Science
Costs
Data Storage Equipment
Energy Resources
Feature Extraction
Neural Networks
Neurons
Plasticity
Time Series Analysis

Publicaties

Recent
Liu, S., Chen, T. , Atashgahi, Z., Chen, X., Sokar, G. , Mocanu, E., Pechenizkiy, M., Wang, Z. , & Mocanu, D. C. (2022). Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. In The Tenth International Conference on Learning Representations, ICLR 2022 OpenReview. https://openreview.net/forum?id=RLtqs6pzj1-&noteId=d7CKVDyMGZi
Liu, S., Chen, T. , Atashgahi, Z., Chen, X., Sokar, G. A. Z. N. , Mocanu, E., Pechenizkiy, M., Wang, Z. , & Mocanu, D. C. (2021). FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. Poster session presented at Sparsity in Neural Networks: Advancing Understanding and Practice 2021, Online.
Liu, S., Chen, T., Chen, X. , Atashgahi, Z., Yin, L., Kou, H., Shen, L., Pechenizkiy, M., Wang, Z. , & Mocanu, D. C. (2021). Sparse Training via Boosting Pruning Plasticity with Neuroregeneration (Poster). Poster session presented at Sparsity in Neural Networks: Advancing Understanding and Practice 2021, Online.
Kichler, N. , Atashgahi, Z. , & Mocanu, D. C. (2021). Robustness of sparse MLPs for supervised feature selection (poster). Poster session presented at Sparsity in Neural Networks: Advancing Understanding and Practice 2021, Online.
Atashgahi, Z., Sokar, G. A. Z. N., van der Lee, T. , Mocanu, E. , Mocanu, D. C. , Veldhuis, R. N. J., & Pechenizkiy, M. (2021). Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders (Extended Abstract). In BNAIC/BENELEARN 2021: The 33rd Benelux Conference on Artificial Intelligence and the 30th Belgian Dutch Conference on Machine Learning
Atashgahi, Z. , Mocanu, D. C. , Veldhuis, R. N. J., & Pechenizkiy, M. (2021). Unsupervised Online Memory-free Change-point Detection using an Ensemble of LSTM-Autoencoder-based Neural Networks (Extended Abstract). Paper presented at 8th ACM Celebration of Women in Computing womENcourage, Prague, Czech Republic.
Atashgahi, Z., Sokar, G. A. Z. N., van der Lee, T. , Mocanu, E. , Mocanu, D. C. , Veldhuis, R. N. J., & Pechenizkiy, M. (Accepted/In press). Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders (poster). Poster session presented at Sparsity in Neural Networks: Advancing Understanding and Practice 2021, Online.
Liu, S., Chen, T., Chen, X. , Atashgahi, Z., Yin, L., Kou, H., Shen, L., Pechenizkiy, M., Wang, Z. , & Mocanu, D. C. (2021). Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. In Advances in Neural Information Processing Systems
Liu, S., van der Lee, T., Yaman, A. , Atashgahi, Z., Ferraro, D., Sokar, G. A. Z. N., Pechenizkiy, M. , & Mocanu, D. C. (2020). Topological Insights into Sparse Neural Networks. Paper presented at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020. https://arxiv.org/abs/2006.14085

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Bezoekadres

Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (gebouwnr. 11)
Hallenweg 19
7522NH  Enschede

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Postadres

Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
Postbus 217
7500 AE Enschede

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