Miguel Lázaro-Gredilla

According to our database1, Miguel Lázaro-Gredilla authored at least 40 papers between 2006 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2018
Cortical Microcircuits from a Generative Vision Model.
CoRR, 2018

Variational Rejection Sampling.
CoRR, 2018

Variational Rejection Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics.
CoRR, 2017

Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Laplace Approximation for Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Hierarchical compositional feature learning.
CoRR, 2016

2015
Local Expectation Gradients for Black Box Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Biophysical parameter retrieval with warped Gaussian processes.
Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium, 2015

2014
Divisive Gaussian Processes for Nonstationary Regression.
IEEE Trans. Neural Netw. Learning Syst., 2014

A Gaussian Process Model for Data Association and a Semidefinite Programming Solution.
IEEE Trans. Neural Netw. Learning Syst., 2014

A Bayesian approach for adaptive multiantenna sensing in cognitive radio networks.
Signal Processing, 2014

Retrieval of Biophysical Parameters With Heteroscedastic Gaussian Processes.
IEEE Geosci. Remote Sensing Lett., 2014

Doubly Stochastic Variational Bayes for non-Conjugate Inference.
Proceedings of the 31th International Conference on Machine Learning, 2014

Laplace approximation with Gaussian Processes for volatility forecasting.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

2013
Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances.
IEEE Signal Process. Mag., 2013

Gaussian Processes for Nonlinear Signal Processing
CoRR, 2013

Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Estimation of vegetation chlorophyll content with Variational Heteroscedastic Gaussian Processes.
Proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, 2013

2012
Kernel Recursive Least-Squares Tracker for Time-Varying Regression.
IEEE Trans. Neural Netw. Learning Syst., 2012

Overlapping Mixtures of Gaussian Processes for the data association problem.
Pattern Recognition, 2012

Low-cost model selection for SVMs using local features.
Eng. Appl. of AI, 2012

Bayesian Warped Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Estimation of the forgetting factor in kernel recursive least squares.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Bayesian multiantenna sensing for cognitive radio.
Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, 2012

2011
Adaptive One-Class Support Vector Machine.
IEEE Trans. Signal Processing, 2011

Support Vector Machines With Constraints for Sparsity in the Primal Parameters.
IEEE Trans. Neural Networks, 2011

Overlapping Mixtures of Gaussian Processes for the Data Association Problem
CoRR, 2011

Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Heteroscedastic Gaussian process regression using expectation propagation.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

A Bayesian approach to tracking with kernel recursive least-squares.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

A block-based approach to adaptively bias the weights of adaptive filters.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Variational Heteroscedastic Gaussian Process Regression.
Proceedings of the 28th International Conference on Machine Learning, 2011

Tracking performance of adaptively biased adaptive filters.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Adaptively biasing the weights of adaptive filters.
IEEE Trans. Signal Processing, 2010

Marginalized neural network mixtures for large-scale regression.
IEEE Trans. Neural Networks, 2010

Sparse Spectrum Gaussian Process Regression.
Journal of Machine Learning Research, 2010

2009
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
A Single Layer Perceptron Approach to Selective Multi-task Learning.
Proceedings of the Bio-inspired Modeling of Cognitive Tasks, 2007

2006
A new cost function to build MLPs by means of regularized boosting.
Proceedings of the Second IASTED International Conference on Computational Intelligence, 2006


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