Publications
- A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models, AIstats 2012
M. E. Khan, S. Mohamed, B. Marlin, and K. Murphy
[ pdf ] [ poster ] [ code ] [ datasets]
- Piecewise Bounds for Estimating Bernoulli-Logistic Latent Gaussian Models, ICML 2011
B. Marlin, M. E. Khan, and K. Murphy
[ pdf ] [ presentation ] [ poster ] [ code ] [ appendix ]
- Variational Bounds for Mixed-Data Factor Analysis, NIPS 2010.
M. E. Khan, B. Marlin, G. Bouchard, and K. Murphy
[ pdf ] [ poster ] [ MATLAB code ] [ corrected version ]
Our implementation for mixture model had a bug, the corrected version contains new results.
- Accelerating Bayesian Structural Inference for Non-decomposable Gaussian Graphical Model, NIPS 2009 (oral)
B. Mogaddham, B. Marlin, M. E. Khan and K. Murphy
[ pdf ] [ poster ] [ MATLAB code (Ben’s website) ]
- An Expectation-Maximization Algorithm Based Kalman Smoother Approach for Event-Related Desynchronization (ERD) Estimation from EEG, Vol. 54, No. 7, July 2007, IEEE Transactions on Biomedical Engineering
M. E. Khan and D. N. Dutt
[ pdf ] [ MATLAB code ]
- State Estimation with Wireless Devices, Third Int. Conf. Intelligent Sensing and Information Processing (ICISIP), 14-17 December 2005, Bangalore , India.
M. E. Khan, H. Raghavan, J. Brahmajosyula, S. K. Ramalingam, S. Narasimhan
[ pdf ]
- Expectation-Maximization (EM) Algorithm for Instantaneous Frequency Estimation with Kalman Smoother, EUSIPCO 2004
M. E. Khan and D. N. Dutt
pdf
- Estimation of ERS/ERD with Kalman Smoother: An EM Algorithm Approach, BIOSIGNAL 2004
M. E. Khan and D. N. Dutt
Technical Reports and Talks
- 08 Feb 2012: A tutorial report on Approximate message passing from my talk on DNOISE.
- 29 Sep 2011: Talk at Microsoft Research, Redmond [ video ] [ slides ]
- 29 Jun 2011: Talk at ICML 2011 [ video ] [ slides ]
- 22 Apr 2011: Derivation of an EM algorithm for Latent Gaussian Model with Gaussian Likelihood [ pdf ]
- 14 Sep 2009: Derivation of Variational EM algorithm for Correlated Topic Model [ pdf ]
- 25 Feb 2009: Derivation of Gaussian likelihood with Gaussian prior on mean [ pdf ]
- 29 Jan 2009: A note on empirical Bayes estimate of Covariance for Multivariate Normal Distribution [ pdf ]
- 24 Dec 2008: Tech report on Bayesian search algorithms for decomposable Guassian graphical model [ pdf ]
- 27 Feb 2008: Updating Inverse of a Matrix when a Column is added/removed [ pdf ] [ code ]
- 25 Feb 2008: Talk on Kalman filter and demo code [ Slides ] [ Demo ]
- 25 Feb 2008: Notes on information filter [ pdf ]
- 30 Oct 2007: Presentation on Variational Bayes and Message passing at Machine learning Reading Group [ slides ]
- 02 Oct 2007: A note on Exchangeability, Polya’s Urn, and De-Finetti’s Theorem [ pdf ]
- 28 Sep 2007: Linear Algebra Tutorial [ Outline ] [ slides ]
- 18 Sep 2007: Probability Tutorial [ Outline ] [ Slides ]
- 14 June 2007: Talk on Brain-Computer Interface, CIFAR Time-series Workshop, Toronto [ slides ]
- 18 May 2007: Talk on Signal Compression and JPEG, UDLS [ Abstract ] [ slides ]
- April 2007: Compressed Sensing, Compressed Classification and Joint Signal Recovery, Machine Learning course project [ pdf ]
- April 2007: Gibbs Sampling for the Probit Regression Model with Gaussian Markov Random Field Latent Variables, Statistical Computation course project [ pdf ] [ slides ]
- 26 Jan 2007: Talk on "Introduction to probability theory, UDLS [ slides ] [ Abstract ]
- Dec 2007: Game theory models for Pursuit-evasion games, Multi-agent systems course project [ pdf ]
- Dec 2007: An incremental deployment algorithm for mobile sensors, Optimization course project [ pdf ]
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