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Hanie Sedghi
Hanie Sedghi
Senior Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Beating the perils of non-convexity: Guaranteed training of neural networks using tensor methods
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1506.08473, 2015
2322015
What is being transferred in transfer learning?
B Neyshabur, H Sedghi, C Zhang
Neural Information Processing Systems (NeurIPS), 2020
2282020
The Singular Values of Convolutional Layers
H Sedghi, V Gupta, PM Long
arXiv preprint arXiv:1805.10408, 2018
1672018
Provable tensor methods for learning mixtures of generalized linear models
H Sedghi, M Janzamin, A Anandkumar
Artificial Intelligence and Statistics, 1223-1231, 2016
852016
Provable Methods for Training Neural Networks with Sparse Connectivity
H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2693, 2014
782014
Generalization bounds for deep convolutional neural networks
PM Long, H Sedghi
International Conference on Learning Representations, 2020
722020
Statistical Structure Learning to Ensure Data Integrity in Smart Grid
H Sedghi, E Jonckheere
IEEE Transactions on Smart Grid 6 (4), 1924-1933, 2015
662015
Exploring the Limits of Large Scale Pre-training
S Abnar, M Dehghani, B Neyshabur, H Sedghi
International Conference on Learning Representations, 2022
532022
Statistical structure learning of smart grid for detection of false data injection
H Sedghi, E Jonckheere
2013 IEEE Power & Energy Society General Meeting, 1-5, 2013
452013
Score Function Features for Discriminative Learning: Matrix and Tensor Framework
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2863, 2014
432014
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks
R Entezari, H Sedghi, O Saukh, B Neyshabur
International Conference on Learning Representations, 2022
372022
The Deep Bootstrap Framework: Good Online Learners are Good Offline Generalizers
P Nakkiran, B Neyshabur, H Sedghi
International Conference on Learning Representations, 2021
37*2021
The intriguing role of module criticality in the generalization of deep networks
NS Chatterji, B Neyshabur, H Sedghi
International Conference on Learning Representations, 2020
342020
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance
S Garg, S Balakrishnan, ZC Lipton, B Neyshabur, H Sedghi
International Conference on Learning Representations, 2022
302022
A game-theoretic approach for power allocation in bidirectional cooperative communication
M Janzamin, MR Pakravan, H Sedghi
2010 IEEE Wireless Communication and Networking Conference, 1-6, 2010
282010
Sysml: The new frontier of machine learning systems
A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ...
242019
Generalization bounds for neural networks through tensor factorization
M Janzamin, H Sedghi, A Anandkumar
CoRR, abs/1506.08473 1, 2015
222015
Training Input-Output Recurrent Neural Networks through Spectral Methods
H Sedghi, A Anandkumar
arXiv preprint arXiv:1603.00954, 2016
192016
Multi-step stochastic ADMM in high dimensions: Applications to sparse optimization and matrix decomposition
H Sedghi, A Anandkumar, E Jonckheere
Advances in neural information processing systems 3 (January), 2771-2779, 2014
192014
Generalization bounds for deep convolutional neural networks
PM Long, H Sedghi
arXiv preprint arXiv:1905.12600, 2019
16*2019
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