Hanie Sedghi
Hanie Sedghi
Research Scientist, Google Brain
Dirección de correo verificada de google.com
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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
1782015
The Singular Values of Convolutional Layers
H Sedghi, V Gupta, PM Long
arXiv preprint arXiv:1805.10408, 2018
772018
Provable Methods for Training Neural Networks with Sparse Connectivity
H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2693, 2014
682014
Provable tensor methods for learning mixtures of generalized linear models
H Sedghi, M Janzamin, A Anandkumar
Artificial Intelligence and Statistics, 1223-1231, 2016
632016
Statistical Structure Learning to Ensure Data Integrity in Smart Grid
H Sedghi, E Jonckheere
IEEE Transactions on Smart Grid 6 (4), 1924-1933, 2015
422015
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
332013
Score function features for discriminative learning: Matrix and tensor framework
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2863, 2014
322014
Score function features for discriminative learning: Matrix and tensor framework
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2863, 2014
322014
Score Function Features for Discriminative Learning: Matrix and Tensor Framework
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2863, 2014
322014
Score Function Features for Discriminative Learning: Matrix and Tensor Framework
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2863, 2014
322014
Score Function Features for Discriminative Learning: Matrix and Tensor Framework
M Janzamin, H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.2863, 2014
322014
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
262010
Generalization bounds for neural networks through tensor factorization
M Janzamin, H Sedghi, A Anandkumar
CoRR, abs/1506.08473 1, 2015
202015
Training Input-Output Recurrent Neural Networks through Spectral Methods
H Sedghi, A Anandkumar
arXiv preprint arXiv:1603.00954, 2016
182016
Generalization bounds for deep convolutional neural networks
PM Long, H Sedghi
arXiv preprint arXiv:1905.12600, 2019
16*2019
Provable tensor methods for learning mixtures of classifiers
H Sedghi, A Anandkumar
arXiv preprint arXiv:1412.3046, 2014
142014
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, 2771-2779, 2014
132014
SysML: The New Frontier of Machine Learning Systems.
A Ratner, D Alistarh, G Alonso, DG Andersen, P Bailis, S Bird, N Carlini, ...
112019
On the Conditional Mutual Information in the Gaussian–Markov Structured Grids
H Sedghi, E Jonckheere
Information and Control in Networks, 277-297, 2014
102014
The intriguing role of module criticality in the generalization of deep networks
NS Chatterji, B Neyshabur, H Sedghi
arXiv preprint arXiv:1912.00528, 2019
92019
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Artículos 1–20