Bala Rajaratnam

According to our database1, Bala Rajaratnam authored at least 27 papers between 2006 and 2019.

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

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2019
A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data.
Machine Learning, 2019

2017
Two-Stage Sampling, Prediction and Adaptive Regression via Correlation Screening.
IEEE Trans. Information Theory, 2017

Generalized Pseudolikelihood Methods for Inverse Covariance Estimation.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.
Proceedings of the IEEE, 2016

Critical exponents of graphs.
J. Comb. Theory, Ser. A, 2016

Large-scale correlation mining for biomolecular network discovery.
Proceedings of the Big Data over Networks, 2016

2015
Differential calculus on graphon space.
J. Comb. Theory, Ser. A, 2015

Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS).
CoRR, 2015

2014
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection.
CoRR, 2014

Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Best permutation analysis.
J. Multivariate Analysis, 2013

A note on the lack of symmetry in the graphical lasso.
Computational Statistics & Data Analysis, 2013

Two-stage variable selection for molecular prediction of disease.
Proceedings of the 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2013

Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Hub Discovery in Partial Correlation Graphs.
IEEE Trans. Information Theory, 2012

Positive Definite Completion Problems for Bayesian Networks.
SIAM J. Matrix Analysis Applications, 2012

Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
CoRR, 2012

Successive Standardization of Rectangular Arrays.
Algorithms, 2012

Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation.
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

Natural order recovery for banded covariance models.
Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, 2012

2011
A local dependence measure and its application to screening for high correlations in large data sets.
Proceedings of the 14th International Conference on Information Fusion, 2011

Successive Normalization of Rectangular Arrays: Rates of Convergence.
Proceedings of the First International Conference on Data Compression, 2011

2010
Learning mixture models via component-wise parameter smoothing.
Computational Statistics & Data Analysis, 2010

2009
Theory and Practice of Expectation Maximization (EM) Algorithm.
Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

2008
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

Component-wise parameter smoothing for learning mixture models.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

2006
Stability Region Based Expectation Maximization for Model-based Clustering.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006


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