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All publications by Ruslan Salakhutdinov
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Multimodal Neural Language Models
Ryan Kiros, Ruslan Salakhutdinov and Rich Zemel
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Tensor Analyzers
Yichuan Tang, Ruslan Salakhutdinov and Geoffrey Hinton
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


One-shot learning by inverting a compositional causal process
Brenden M. Lake, Ruslan Salakhutdinov and Josh Tenenbaum
Advances in Neural Information Processing Systems 26, 2013


Discriminative Transfer Learning with Tree-based Priors
Nitish Srivastava and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 26, 2013


Learning Stochastic Feedforward Neural Networks
Yichuan Tang and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 26, 2013


The Power of Asymmetry in Binary Hashing
Behnam Neyshabur, Nati Srebro, Ruslan Salakhutdinov, Yury Makarychev and Payman Yadollahpour
Advances in Neural Information Processing Systems 26, 2013


Annealing between distributions by averaging moments
Roger B. Grosse, Chris J. Maddison and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 26, 2013


Cardinality Restricted Boltzmann Machines
Kevin Swersky, Ilya Sutskever, Daniel Tarlow, Richard S. Zemel, Ruslan Salakhutdinov and Ryan P. Adams
Advances in Neural Information Processing Systems 25, 2012


A Better Way to Pretrain Deep Boltzmann Machines
Geoffrey E. Hinton and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 25, 2012


Multimodal Learning with Deep Boltzmann Machines
Nitish Srivastava and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 25, 2012


Hamming Distance Metric Learning
Mohammad Norouzi, David Fleet and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 25, 2012


Matrix reconstruction with the local max norm
Rina Foygel, Nathan Srebro and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 25, 2012


Deep Lambertian Networks
Yichuan Tang, Geoffrey E. Hinton and Ruslan Salakhutdinov
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Deep Mixtures of Factor Analysers
Yichuan Tang, Geoffrey E. Hinton and Ruslan Salakhutdinov
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Domain Adaptation: A Small Sample Statistical Approach
Ruslan Salakhutdinov, Sham M. Kakade and Dean P. Foster
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Learning with the weighted trace-norm under arbitrary sampling distributions
Rina Foygel, Ohad Shamir, Nati Srebro and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 24, 2011


Learning to Learn with Compound HD Models
Antonio Torralba, Joshua B. Tenenbaum and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 24, 2011


Transfer Learning by Borrowing Examples for Multiclass Object Detection
Joseph J. Lim, Ruslan Salakhutdinov and Antonio Torralba
Advances in Neural Information Processing Systems 24, 2011


Learning Deep Boltzmann Machines using Adaptive MCMC
Ruslan Salakhutdinov
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
Nathan Srebro and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 23, 2010


Practical Large-Scale Optimization for Max-norm Regularization
Jason Lee, Ben Recht, Nathan Srebro, Joel Tropp and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 23, 2010


Efficient Learning of Deep Boltzmann Machines
Ruslan Salakhutdinov and Hugo Larochelle
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Workshop summary: Workshop on learning feature hierarchies
Kay Yu, Ruslan Salakhutdinov, Yann Lecun, Geoffrey E. Hinton and Yoshua Bengio
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Evaluation methods for topic models
Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov and David M. Mimno
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Learning nonlinear dynamic models
John Langford, Ruslan Salakhutdinov and Tong Zhang
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Modelling Relational Data using Bayesian Clustered Tensor Factorization
Ilya Sutskever, Joshua B. Tenenbaum and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 22, 2009


Replicated Softmax: an Undirected Topic Model
Geoffrey E. Hinton and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 22, 2009


Learning in Markov Random Fields using Tempered Transitions
Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 22, 2009


Deep Boltzmann Machines
Ruslan Salakhutdinov and Geoffrey E. Hinton
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Ruslan Salakhutdinov and Andriy Mnih
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


On the quantitative analysis of deep belief networks
Ruslan Salakhutdinov and Iain Murray
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Evaluating probabilities under high-dimensional latent variable models
Iain Murray and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 21, 2008


Restricted Boltzmann machines for collaborative filtering
Ruslan Salakhutdinov, Andriy Mnih and Geoffrey E. Hinton
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
Geoffrey E. Hinton and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 20, 2007


Probabilistic Matrix Factorization
Andriy Mnih and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 20, 2007


Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure
Ruslan Salakhutdinov and Geoffrey E. Hinton
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Neighbourhood Components Analysis
Jacob Goldberger, Geoffrey E. Hinton, Sam T. Roweis and Ruslan Salakhutdinov
Advances in Neural Information Processing Systems 17, 2004


Optimization with EM and Expectation-Conjugate-Gradient
Ruslan Salakhutdinov, Sam T. Roweis and Zoubin Ghahramani
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003


Adaptive Overrelaxed Bound Optimization Methods
Ruslan Salakhutdinov and Sam T. Roweis
Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003