Mohammad Emtiyaz Khan
Affiliations:- RIKEN Center for Advanced Intelligence, Tokyo, Japan
- EPFL, Lausanne, Switzerland
- University of British Columbia, Department of Computer Science, Vancouver, BC, Canada
According to our database1,
Mohammad Emtiyaz Khan
authored at least 59 papers
between 2004 and 2024.
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Bibliography
2024
2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
2021
CoRR, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of The 11th Asian Conference on Machine Learning, 2019
2018
CoRR, 2018
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models.
Proceedings of the International Symposium on Information Theory and Its Applications, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Proceedings of the 2017 IEEE Symposium on Security and Privacy, 2017
Conjugate-Computation Variational Inference: Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016
2015
Convergence of Proximal-Gradient Stochastic Variational Inference under Non-Decreasing Step-Size Sequence.
CoRR, 2015
2014
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
Proceedings of the Sixth Asian Conference on Machine Learning, 2014
2013
Proceedings of the 30th International Conference on Machine Learning, 2013
2012
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
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
2011
Proceedings of the 28th International Conference on Machine Learning, 2011
2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
2009
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models.
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
An Expectation-Maximization Algorithm Based Kalman Smoother Approach for Event-Related Desynchronization (ERD) Estimation from EEG.
IEEE Trans. Biomed. Eng., 2007
2004
Expectation-maximization (EM) algorithm for instantaneous frequency estimation with Kalman smoother.
Proceedings of the 2004 12th European Signal Processing Conference, 2004