Andriy Mnih
Research Associate
Gatsby Computational Neuroscience Unit
University College London
email: Can be easily derived from the URL for this page.
About me
I am a postdoctoral researcher at Gatsby, working with Yee Whye Teh. Before coming to
Gatsby, I was a PhD student in the Machine Learning Group at the
University of Toronto, advised by Geoffrey Hinton.
Research interests
- collaborative filtering
- statistical language modelling
- undirected graphical models
- large-scale Bayesian learning methods
Publications
Learning Label Trees for Probabilistic Modelling of Implicit Feedback
Andriy Mnih and Yee Whye Teh
Advances in Neural Information Processing Systems 25 (NIPS 2012)
[pdf]
[poster]
[bibtex]
A fast and simple algorithm for training neural probabilistic language models
Andriy Mnih and Yee Whye Teh
International Conference on Machine Learning 2012 (ICML 2012)
[pdf]
[slides]
[poster]
[bibtex]
[5 min talk]
Taxonomy-Informed Latent Factor Models for Implicit Feedback
Andriy Mnih
JMLR W&CP Volume 18: Proceedings of KDD Cup 2011
[pdf]
[slides]
[bibtex]
Improving a Statistical Language Model Through Non-linear Prediction
Andriy Mnih, Zhang Yuecheng, and Geoffrey Hinton
Neurocomputing, 72:7-9, 2009
[bibtex]
A Scalable Hierarchical Distributed Language Model
Andriy Mnih and Geoffrey Hinton
Advances in Neural Information Processing Systems 21 (NIPS 2008)
[pdf]
[bibtex]
Bayesian Probabilistic Matrix Factorization using Markov Chain Monte Carlo
Ruslan Salakhutdinov and Andriy Mnih
International Conference on Machine Learning 2008 (ICML 2008)
[pdf]
[bibtex]
Improving a Statistical Language Model by Modulating the Effects of Context Words
Zhang Yuecheng, Andriy Mnih, and Geoffrey Hinton
European Symposium on Artificial Neural Networks 2008 (ESANN 2008)
Probabilistic Matrix Factorization
Ruslan Salakhutdinov and Andriy Mnih
Advances in Neural Information Processing Systems 20 (NIPS 2007)
[pdf]
[bibtex]
Three New Graphical Models for Statistical Language Modelling
Andriy Mnih and Geoffrey Hinton
International Conference on Machine Learning 2007 (ICML 2007)
[pdf]
[bibtex]
Restricted Boltzmann Machines for Collaborative Filtering
Ruslan Salakhutdinov, Andriy Mnih, and Geoffrey Hinton
International Conference on Machine Learning 2007 (ICML 2007)
[pdf]
[bibtex]
Visualizing Similarity Data with a Mixture of Maps
James Cook, Ilya Sutskever, Andriy Mnih, and Geoffrey Hinton
AI and Statistics 2007 (AISTATS 2007)
[pdf]
[bibtex]
Learning Nonlinear Constraints with Contrastive Backpropagation
Andriy Mnih and Geoffrey Hinton
International Joint Conference on Neural Networks 2005 (IJCNN 2005)
[bibtex]
Wormholes Improve Contrastive Divergence
Geoffrey Hinton, Max Welling, and Andriy Mnih
Advances in Neural Information Processing Systems 16 (NIPS 2003)
[bibtex]