Nitish Srivastava
Nitish Srivastava
Verified email at cs.toronto.edu - Homepage
Title
Cited by
Cited by
Year
Dropout: a simple way to prevent neural networks from overfitting
N Srivastava, G Hinton, A Krizhevsky, I Sutskever, R Salakhutdinov
The journal of machine learning research 15 (1), 1929-1958, 2014
218412014
Improving neural networks by preventing co-adaptation of feature detectors
GE Hinton, N Srivastava, A Krizhevsky, I Sutskever, RR Salakhutdinov
arXiv preprint arXiv:1207.0580, 2012
52492012
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
T Tieleman, G Hinton
COURSERA: Neural networks for machine learning 4 (2), 26-31, 2012
37092012
Unsupervised learning of video representations using lstms
N Srivastava, E Mansimov, R Salakhudinov
International conference on machine learning, 843-852, 2015
15562015
Multimodal learning with deep boltzmann machines
N Srivastava, RR Salakhutdinov
Advances in neural information processing systems, 2222-2230, 2012
14012012
Neural networks for machine learning lecture 6a overview of mini-batch gradient descent
G Hinton, N Srivastava, K Swersky
Cited on 14 (8), 2012
339*2012
Improving neural networks with dropout
N Srivastava
University of Toronto 182 (566), 7, 2013
2132013
Discriminative transfer learning with tree-based priors
N Srivastava, RR Salakhutdinov
Advances in neural information processing systems, 2094-2102, 2013
1902013
Modeling documents with deep boltzmann machines
N Srivastava, RR Salakhutdinov, GE Hinton
arXiv preprint arXiv:1309.6865, 2013
1822013
Exploiting image-trained CNN architectures for unconstrained video classification
S Zha, F Luisier, W Andrews, N Srivastava, R Salakhutdinov
arXiv preprint arXiv:1503.04144, 2015
1812015
Learning representations for multimodal data with deep belief nets
N Srivastava, R Salakhutdinov
International conference on machine learning workshop 79, 2012
1722012
Lecture 6a overview of mini–batch gradient descent
G Hinton, N Srivastava, K Swersky
Coursera Lecture slides https://class. coursera. org/neuralnets-2012-001 …, 2012
1422012
Improving neural networks by preventing co-adaptation of feature detectors (2012)
GE Hinton, N Srivastava, A Krizhevsky, I Sutskever, RR Salakhutdinov
arXiv preprint arXiv:1207.0580, 2012
1062012
Improving neural networks by preventing co-adaptation of feature detectors. arXiv 2012
GE Hinton, N Srivastava, A Krizhevsky, I Sutskever, RR Salakhutdinov
arXiv preprint arXiv:1207.0580, 0
86
Learning generative models with visual attention
C Tang, N Srivastava, RR Salakhutdinov
Advances in Neural Information Processing Systems, 1808-1816, 2014
762014
Enriching textbooks through data mining
R Agrawal, S Gollapudi, K Kenthapadi, N Srivastava, R Velu
Proceedings of the First ACM Symposium on Computing for Development, 1-9, 2010
542010
Ilya Sutskever, Ruslan, Salakhutdinov
N Srivastava, G Hinton, A Krizhevsky
Dropout: a simple way to prevent neural networks from overfitting, 1929-1958, 1929
401929
Initialization strategies of spatio-temporal convolutional neural networks
E Mansimov, N Srivastava, R Salakhutdinov
arXiv preprint arXiv:1503.07274, 2015
322015
System and method for addressing overfitting in a neural network
GE Hinton, A Krizhevsky, I Sutskever, N Srivastva
US Patent 9,406,017, 2016
312016
Modeling inter-individual variability in sugar beet populations
P De Reffye, S Lemaire, N Srivastava, F Maupas, PH Cournède
2009 Third International Symposium on Plant Growth Modeling, Simulation …, 2009
102009
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