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All publications by Laurens Maaten
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Learning with Marginalized Corrupted Features
Laurens Maaten, Minmin Chen, Stephen Tyree and Kilian Q. Weinberger
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Learning Discriminative Fisher Kernels
Laurens Maaten
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Hidden-Unit Conditional Random Fields
Laurens Maaten, Max Welling and Lawrence K. Saul
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Discussion of "Spectral Dimensionality Reduction via Maximum Entropy"
Laurens Maaten
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11), 2011


Deep Supervised t-Distributed Embedding
Martin R. Min, Laurens Maaten, Zineng Yuan, Anthony J. Bonner and Zhaolei Zhang
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010


Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
Diane Hu, Laurens Maaten, Youngmin Cho, Sorin Lerner and Lawrence K. Saul
Advances in Neural Information Processing Systems 23, 2010


On Herding and the Perceptron Cycling Theorem
Andrew Gelfand, Yutian Chen, Laurens Maaten and Max Welling
Advances in Neural Information Processing Systems 23, 2010


Learning a Parametric Embedding by Preserving Local Structure
Laurens Maaten
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009