Google, dblp

2014

S. Seth, N. Valimaki, S. Kaski, A. Honkela, Differential analysis of whole-metagenome shotgun sequences, in International Workshop on Machine Learning in Systems Biology 2014.

S. Seth, J. Shawe-Taylor, S. Kaski, Retrieval of experiments by efficient estimation of marginal likelihood, in International Conference on Neural Information Processing 2014. [arXiv]

S. Seth, N. Valimaki, S. Kaski, A. Honkela, Exploration and retrieval of whole-metagenome sequencing samples, in Bioinformatics, 2014. [arXiv] [code]

R. Pokharel, S. Seth, J. C. Principe, Quantized mixture kernel least mean square, in IEEE International Joint Conference on Neural Networks (IJCNN), 2014.

S. Seth, J. C. Principe, Learning dependence from samples, in International Journal of Bioinformatics Research and Applications, 2014.

I. Park, S. Seth, S. Vaerenbergh, Probabilistic kernel least mean squares algorithms, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014.

2013

S. Seth, M. J. A. Eugster, Probabilistic archetypal analysis, in arXiv. [code]

R. Dutta, S. Seth, S. Kaski, Retrieval of experiments with sequential Dirichlet process mixtures in model  space, in arXiv.

I. Park, S. Seth, S. Vaerenbergh, Bayesian extensions of kernel least mean squares, in arXiv.

I. Park, S. Seth, A. R. C. Paiva, L. Li, J. C. Principe, Kernel methods on spike train space for neuroscience: a tutorial, in IEEE Signal Processing Magazine, 2013.

R. Pokharel, S. Seth, J. C. Principe, Mixture kernel least mean square, in IEEE International Joint Conference on Neural Networks (IJCNN), 2013.

2012

B. Fadlallah, S. Seth, A. Keil, J. C. Principe, Quantifying cognitive state from EEG using dependence measures, in IEEE Transactions on Biomedical Engineering, 2012.

B. Fadlallah, A. J. Brockmeier, S. Seth, L. Li, A. Keil, J. C. Principe, An association framework to analyze dependence structure in time series, in International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2012.

B. Chen, S. Zhao, S. Seth, J. C. Principe, Online efficient learning with quantized KLMS and L1 regularization, in IEEE International Joint Conference on Neural Networks (IJCNN), 2012.

I. Park, S. Seth, M. Rao, J. C. Principe, Strictly positive definite spike train kernels for point process divergence, in Neural Computation, 2012. [description and code]

S. Seth, J. C. Principe, Conditional association, in Neural Computation, 2012. [description and code]

B. Fadlallah, S. Seth, A. Keil, J. C. Principe, Analying dependence structure of  the human brain in response to visual stimuli, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012.

L. Li, I. Park, S. Seth, J. C. Sanchez, J. C. Principe, Functional connectivity dynamics among cortical neurons: A dependency analysis, in IEEE Transactions on Neural and Rehabilitation Systems Engineering, 2012

S. Seth, J. C. Principe, Assessing Granger non-causality using nonparametric measure of conditional independence, in IEEE Transactions on Neural Networks and Learning Systems, 2012. [description and code]

2011

S. Seth, On nonparametric measures of dependence and conditional independence: Theory and applications, Doctoral dissertation, University of Florida, 2011. [description]

B. Fadlallah, S. Seth, J. C. Principe, Robust EEG preprocessing for dependence-based condition discrimination, in International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2011.

S. Seth, M. Rao, I. Park, J. C. Principe, A unified framework for quadratic measures of independence, in IEEE Transactions on Signal Processing, 2011. [description and code]

S. Seth, A. Brockmeier, J. Choi, M. Semework, J. Francis, J. C. Principe, Evaluating dependence in spike train metric spaces, in IEEE International Joint Conference on Neural Networks (IJCNN), 2011. [description and code]

V. Bolon-Canedo, S. Seth, N. Sanchez-Marono, A Alonso-Betanzos, J. C. Principe, Statistical dependence measure for feature selection in microarray datasets, European Symposium on Artificial Neural Networks (ESANN), 2011.

I. Park, S. Seth, M. Rao, J. C. Principe, Estimating symmetric chi-square divergence for point processes, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011. 

S. Seth, A. J. Brockmeier, J. C. Principe, A metric based approach toward point process divergence, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011.

M. Rao, S. Seth, J.-W. Xu, Y. Chen, H. Tagare, J. C. Principe, A test of independence based on a generalized correlation function, in Signal Processing, 2011. [description and code]

2010

J. C. Principe, W. Liu, P. Pokharel, J.-W. Xu, S. Seth, Correntropy for random variables: properties and applications in statistical inference, Information Theoretic Learning: Renyi's Entropy and Kernel Perspectives, J. C. Principe, Springer Verlag, 2010 (Chapter 10).

S. Seth, I. Park, A. Brockmeier, M. Semework, J. Choi, J. Francis, J. C. Principe, A novel family of non-parametric cumulative based divergences for point processes, in Advances in Neural Information Processing Systems (NIPS), 2010. [description and code]

S. Seth, J. C. Principe, Variable Selection: A statistical dependence perspective, in International Conference on Machine Learning and Applications (ICMLA), 2010. [link]

2009

2008