Ruslan Salakhutdinov

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Geoffrey HintonEmeritus Prof. Comp Sci, U.Toronto & Engineering Fellow, GoogleVerified email at cs.toronto.edu
Nitish SrivastavaResearch Scientist, AppleVerified email at cs.toronto.edu
Zhilin YangCarnegie Mellon UniversityVerified email at cs.cmu.edu
Richard ZemelProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
William W. CohenGoogle AIVerified email at google.com
Yao-Hung Hubert TsaiCarnegie Mellon University PhD StudentVerified email at andrew.cmu.edu
Ilya SutskeverCo-Founder and Chief Scientist of OpenAIVerified email at openai.com
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Jamie KirosCo-Founder, StartupVerified email at google.com
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
Devendra Singh ChaplotCarnegie Mellon University, Facebook AI ResearchVerified email at fb.com
Jimmy BaUniversity of TorontoVerified email at cs.toronto.edu
Joshua B. TenenbaumMITVerified email at mit.edu
Kyunghyun ChoNew York University, GenentechVerified email at nyu.edu
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Antonio TorralbaProfessor of Computer Science, MITVerified email at csail.mit.edu
Zhiting HuAssistant Professor at UC San DiegoVerified email at ucsd.edu
Emilio ParisottoCarnegie Mellon UniversityVerified email at cs.cmu.edu
Aaron CourvilleAssociate Professor, DIRO, Université de Montréal, Mila, Cifar CAI chairVerified email at umontreal.ca
Sam Roweis (Memorial)New York UniversityVerified email at buffalo.edu

Ruslan Salakhutdinov

UPMC Professor, Machine Learning Department, CMU

Verified email at cs.cmu.edu - Homepage

Machine Learning Artificial Intelligence Deep Learning


Title Sort by citations Sort by year Sort by 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	37632	2014
Reducing the dimensionality of data with neural networks GE Hinton, RR Salakhutdinov science 313 (5786), 504-507, 2006	18266	2006
Show, attend and tell: Neural image caption generation with visual attention K Xu, J Ba, R Kiros, K Cho, A Courville, R Salakhutdinov, RS Zemel, ... International Conference on Machine Learning (ICML) 2 (3), 5, 2015	9317	2015
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	8047	2012
Xlnet: Generalized autoregressive pretraining for language understanding Z Yang, Z Dai, Y Yang, J Carbonell, RR Salakhutdinov, QV Le Advances in neural information processing systems 32, 2019	5193	2019
Probabilistic matrix factorization R Salakhutdinov, A Mnih Neural Information Processing Systems 21, 2007	4757*	2007
Efficient Learning of Deep Boltzmann Machines. R Salakhutdinov, H Larochelle International Conference on Artificial Intelligence and Statistics (AISTATS …, 2010	3629	2010
Deep Boltzmann Machines. R Salakhutdinov, GE Hinton International Conference on Artificial Intelligence and Statistics (AISTATS …, 2009	3420*	2009
Siamese neural networks for one-shot image recognition G Koch, R Zemel, R Salakhutdinov ICML deep learning workshop 2, 0, 2015	3318	2015
Skip-thought vectors R Kiros, Y Zhu, RR Salakhutdinov, R Zemel, R Urtasun, A Torralba, ... Advances in neural information processing systems 28, 2015	2593	2015
Human-level concept learning through probabilistic program induction BM Lake, R Salakhutdinov, JB Tenenbaum Science 350 (6266), 1332-1338, 2015	2559	2015
Unsupervised learning of video representations using lstms N Srivastava, E Mansimov, R Salakhutdinov International Conference on Machine Learning (ICML) 2, 2015	2482	2015
Neighbourhood components analysis J Goldberger, GE Hinton, S Roweis, RR Salakhutdinov Advances in neural information processing systems 17, 2004	2278	2004
Restricted Boltzmann machines for collaborative filtering R Salakhutdinov, A Mnih, G Hinton Proceedings of the 24th international conference on Machine learning, 791-798, 2007	2265	2007
Transformer-xl: Attentive language models beyond a fixed-length context Z Dai, Z Yang, Y Yang, J Carbonell, QV Le, R Salakhutdinov arXiv preprint arXiv:1901.02860, 2019	2102	2019
Unifying visual-semantic embeddings with multimodal neural language models R Kiros, R Salakhutdinov, RS Zemel Transactions of the Association for Computational Linguistics (TACL), 2014	1865*	2014
Multimodal learning with deep boltzmann machines N Srivastava, RR Salakhutdinov Advances in neural information processing systems 25, 2012	1813	2012
Aligning books and movies: Towards story-like visual explanations by watching movies and reading books Y Zhu, R Kiros, R Zemel, R Salakhutdinov, R Urtasun, A Torralba, S Fidler Proceedings of the IEEE international conference on computer vision, 19-27, 2015	1767	2015
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo R Salakhutdinov, A Mnih Proceedings of the 25th international conference on Machine learning, 880-887, 2008	1659	2008
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo R Salakhutdinov, A Mnih Proceedings of the 25th international conference on Machine learning, 880-887, 2008	1659	2008

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