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Zahra Atashgahi
Zahra Atashgahi
Ph.D. candidate at University of Twente
Geverifieerd e-mailadres voor utwente.nl - Homepage
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Sparse Training via Boosting Pruning Plasticity with Neuroregeneration
S Liu, T Chen, X Chen, Z Atashgahi, L Yin, H Kou, L Shen, M Pechenizkiy, ...
NeurIPS2021, Advances in Neural Information Processing Systems, 2021
1072021
Deep ensembling with no overhead for either training or testing: The all-round blessings of dynamic sparsity
S Liu, T Chen, Z Atashgahi, X Chen, G Sokar, E Mocanu, M Pechenizkiy, ...
ICLR2022, The International Conference on Learning Representations, 2021
482021
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders
Z Atashgahi, G Sokar, T van der Lee, E Mocanu, DC Mocanu, R Veldhuis, ...
Machine Learning Journal (ECML-PKDD 2022 journal track), 2021
342021
Topological insights into sparse neural networks
S Liu, T Van der Lee, A Yaman, Z Atashgahi, D Ferraro, G Sokar, ...
ECML-PKDD2020, European Conference on Machine Learning and Principles and …, 2020
342020
A Brain-inspired Algorithm for Training Highly Sparse Neural Networks
Z Atashgahi, J Pieterse, S Liu, D Constantin Mocanu, R Veldhuis, ...
Machine Learning Journal (ECML-PKDD 2022 journal track), 2022
22*2022
Where to Pay Attention in Sparse Training for Feature Selection?
G Sokar, Z Atashgahi, M Pechenizkiy, DC Mocanu
NeurIPS2022, 36th Annual Conference on Neural Information Processing Systems, 2022
132022
Memory-free Online Change-point Detection: A Novel Neural Network Approach
Z Atashgahi, DC Mocanu, R Veldhuis, M Pechenizkiy
arXiv preprint arXiv:2207.03932, 2022
72022
Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks
Z Atashgahi, X Zhang, N Kichler, S Liu, L Yin, M Pechenizkiy, R Veldhuis, ...
TMLR, Transactions on Machine Learning Research, 2023
62023
Abnormal Activity Detection for the Elderly People using ConvLSTM Autoencoder
E Nazerfard, Z Atashgahi, A Nadali
42021
Adaptive sparsity level during training for efficient time series forecasting with transformers
Z Atashgahi, M Pechenizkiy, R Veldhuis, DC Mocanu
arXiv preprint arXiv:2305.18382, 2023
12023
Unsupervised online memory-free change-point detection using an ensemble of LSTM-autoencoder-based neural networks
Z Atashgahi, DC Mocanu, R Veldhuis, M Pechenizkiy
8th ACM Celebration of Women in Computing womENcourage, 2021
12021
Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks
K Liu, Z Atashgahi, G Sokar, M Pechenizkiy, DC Mocanu
International Conference on Artificial Intelligence and Statistics, 3952-3960, 2024
2024
Advancing Efficiency in Neural Networks through Sparsity and Feature Selection
Z Atashgahi
2024
FASTR Feature selection using A Sparse Training Regime
MD Keep, M Pechenizkiy, DC Mocanu, Z Atashgahi, G Sokar
2023
Cost-effective Artificial Neural Networks
Z Atashgahi
IJCAI-23, Doctoral Consortium Track, 2023
2023
Robustness of sparse MLPs for supervised feature selection (poster)
N Kichler, Z Atashgahi, DC Mocanu
Sparsity in Neural Networks: Advancing Understanding and Practice 2021, 2021
2021
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders (poster)
Z Atashgahi, GAZN Sokar, T van der Lee, E Mocanu, DC Mocanu, ...
Sparsity in Neural Networks: Advancing Understanding and Practice 2021, 2021
2021
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Artikelen 1–17