| 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 | 26388 | 2014 |
| 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 | 6143 | 2012 |
| 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 | 4391 | 2012 |
| Unsupervised learning of video representations using lstms N Srivastava, E Mansimov, R Salakhudinov International conference on machine learning, 843-852, 2015 | 1850 | 2015 |
| Multimodal Learning with Deep Boltzmann Machines. N Srivastava, R Salakhutdinov NIPS 1, 2, 2012 | 1268 | 2012 |
| Neural networks for machine learning lecture 6a overview of mini-batch gradient descent G Hinton, N Srivastava, K Swersky Cited on 14 (8), 2012 | 482* | 2012 |
| Multimodal learning with deep Boltzmann machines. N Srivastava, R Salakhutdinov J. Mach. Learn. Res. 15 (1), 2949-2980, 2014 | 332 | 2014 |
| Improving neural networks with dropout N Srivastava University of Toronto 182 (566), 7, 2013 | 231 | 2013 |
| Discriminative Transfer Learning with Tree-based Priors. N Srivastava, R Salakhutdinov NIPS 3 (4), 8, 2013 | 214 | 2013 |
| 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 | 208 | 2012 |
| 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 | 204 | 2015 |
| Modeling documents with deep boltzmann machines N Srivastava, RR Salakhutdinov, GE Hinton arXiv preprint arXiv:1309.6865, 2013 | 194 | 2013 |
| Learning representations for multimodal data with deep belief nets N Srivastava, R Salakhutdinov International conference on machine learning workshop 79, 3, 2012 | 186 | 2012 |
| 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 | 120 | |
| Learning generative models with visual attention Y Tang, N Srivastava, R Salakhutdinov arXiv preprint arXiv:1312.6110, 2013 | 87 | 2013 |
| 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 | 56 | 2010 |
| System and method for addressing overfitting in a neural network GE Hinton, A Krizhevsky, I Sutskever, N Srivastva US Patent 9,406,017, 2016 | 52 | 2016 |
| Initialization strategies of spatio-temporal convolutional neural networks E Mansimov, N Srivastava, R Salakhutdinov arXiv preprint arXiv:1503.07274, 2015 | 36 | 2015 |
| T2S-Tensor: Productively generating high-performance spatial hardware for dense tensor computations N Srivastava, H Rong, P Barua, G Feng, H Cao, Z Zhang, D Albonesi, ... 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019 | 15 | 2019 |
| Capsules with inverted dot-product attention routing YHH Tsai, N Srivastava, H Goh, R Salakhutdinov arXiv preprint arXiv:2002.04764, 2020 | 14 | 2020 |
Ruslan SalakhutdinovUPMC Professor, Machine Learning Department, CMUAdresse e-mail validée de cs.cmu.edu
