Bala Rajaratnam

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 11

Top Topics

Optimization Methods

Top Venues

IEEE Trans. Inf. Theory

J. Comb. Theory, Ser. A

Publications

Yun Wei, Bala Rajaratnam, Alfred O. Hero III
A Unified Framework for Correlation Mining in Ultra-High Dimension. IEEE Trans. Inf. Theory 69 (1) (2023)
Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. ICLR (2023)
Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. CoRR (2022)
Kshitij Khare, Sang-Yun Oh, Syed Rahman, Bala Rajaratnam
A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data. Mach. Learn. 108 (12) (2019)
Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam
Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. AISTATS (2017)
Hamed Firouzi, Alfred O. Hero III, Bala Rajaratnam
Two-Stage Sampling, Prediction and Adaptive Regression via Correlation Screening. IEEE Trans. Inf. Theory 63 (1) (2017)
Dominique Guillot, Apoorva Khare, Bala Rajaratnam
Critical exponents of graphs. J. Comb. Theory, Ser. A 139 (2016)
Alfred O. Hero III, Bala Rajaratnam
Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining. Proc. IEEE 104 (1) (2016)
Brett Naul, Bala Rajaratnam, Dario Vincenzi
The role of the isotonizing algorithm in Stein's covariance matrix estimator. Comput. Stat. 31 (4) (2016)
Peter Diao, Dominique Guillot, Apoorva Khare, Bala Rajaratnam
Differential calculus on graphon space. J. Comb. Theory, Ser. A 133 (2015)
Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III
Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS). CoRR (2015)
Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. NIPS (2014)
Tianxi Li, Chao Gao, Meng Xu, Bala Rajaratnam
Detecting the impact area of BP deepwater horizon oil discharge: an analysis by time varying coefficient logistic models and boosted trees. Comput. Stat. 29 (1) (2014)
Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. CoRR (2014)
Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III
Two-stage variable selection for molecular prediction of disease. CAMSAP (2013)
Benjamin T. Rolfs, Bala Rajaratnam
A note on the lack of symmetry in the graphical lasso. Comput. Stat. Data Anal. 57 (1) (2013)
Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension. AISTATS (2013)
Bala Rajaratnam, Julia Salzman
Best permutation analysis. J. Multivar. Anal. 121 (2013)
Benjamin T. Rolfs, Bala Rajaratnam
Natural order recovery for banded covariance models. SAM (2012)
Benjamin T. Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation. NIPS (2012)
Dominique Guillot, Bala Rajaratnam, Benjamin T. Rolfs, Arian Maleki, Ian Wong
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation CoRR (2012)
Emanuel Ben-David, Bala Rajaratnam
Positive Definite Completion Problems for Bayesian Networks. SIAM J. Matrix Anal. Appl. 33 (2) (2012)
Alfred O. Hero III, Bala Rajaratnam
Hub Discovery in Partial Correlation Graphs. IEEE Trans. Inf. Theory 58 (9) (2012)
Richard A. Olshen, Bala Rajaratnam
Successive Standardization of Rectangular Arrays. Algorithms 5 (1) (2012)
Kumar Sricharan, Alfred O. Hero III, Bala Rajaratnam
A local dependence measure and its application to screening for high correlations in large data sets. FUSION (2011)
Richard A. Olshen, Bala Rajaratnam
Successive Normalization of Rectangular Arrays: Rates of Convergence. CCP (2011)
Chandan K. Reddy, Bala Rajaratnam
Learning mixture models via component-wise parameter smoothing. Comput. Stat. Data Anal. 54 (3) (2010)
Chandan K. Reddy, Bala Rajaratnam
Component-wise parameter smoothing for learning mixture models. ICPR (2008)
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. 30 (7) (2008)
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam
Stability Region Based Expectation Maximization for Model-based Clustering. ICDM (2006)