Search Machine Learning Repository:
All publications by Michalis K. Titsias
authors venues years



Manifold Relevance Determination
Andreas Damianou, Carl Ek, Michalis K. Titsias and Neil D. Lawrence
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Variational Gaussian Process Dynamical Systems
Andreas Damianou, Michalis K. Titsias and Neil D. Lawrence
Advances in Neural Information Processing Systems 24, 2011


Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning
Miguel Lázaro-gredilla and Michalis K. Titsias
Advances in Neural Information Processing Systems 24, 2011


Variational Heteroscedastic Gaussian Process Regression
Michalis K. Titsias and Miguel Lázaro-gredilla
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Bayesian Gaussian Process Latent Variable Model
Michalis K. Titsias and Neil D. Lawrence
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Mauricio A. Álvarez, David Luengo, Michalis K. Titsias and Neil D. Lawrence
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Variational Learning of Inducing Variables in Sparse Gaussian Processes
Michalis K. Titsias
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


Efficient Sampling for Gaussian Process Inference using Control Variables
Neil D. Lawrence, Magnus Rattray and Michalis K. Titsias
Advances in Neural Information Processing Systems 21, 2008


The Infinite Gamma-Poisson Feature Model
Michalis K. Titsias
Advances in Neural Information Processing Systems 20, 2007


Learning About Multiple Objects in Images: Factorial Learning without Factorial Search
Christopher Williams and Michalis K. Titsias
Advances in Neural Information Processing Systems 15, 2002