Bala Rajaratnam

32 papers A* 2A 2B 1C 1Journal 19Unranked 5

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	A Unified Framework for Correlation Mining in Ultra-High Dimension. IEEE Trans. Inf. Theory Yun Wei, Bala Rajaratnam, Alfred O. Hero III
2023	A*	`conf`	Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. ICLR Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
2022	J	`jnl`	Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. CoRR Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo
2019	J	`jnl`	A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data. Mach. Learn. Kshitij Khare, Sang-Yun Oh, Syed Rahman, Bala Rajaratnam
2017	A	`conf`	Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. AISTATS Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam
2017	J	`jnl`	Two-Stage Sampling, Prediction and Adaptive Regression via Correlation Screening. IEEE Trans. Inf. Theory Hamed Firouzi, Alfred O. Hero III, Bala Rajaratnam
2016	J	`jnl`	Critical exponents of graphs. J. Comb. Theory A Dominique Guillot, Apoorva Khare, Bala Rajaratnam
2016	J	`jnl`	Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining. Proc. IEEE Alfred O. Hero III, Bala Rajaratnam
2016	—	`ch.`	Large-scale correlation mining for biomolecular network discovery. Big Data over Networks Alfred O. Hero III, Bala Rajaratnam
2016	J	`jnl`	The role of the isotonizing algorithm in Stein's covariance matrix estimator. Comput. Stat. Brett Naul, Bala Rajaratnam, Dario Vincenzi
2015	J	`jnl`	Differential calculus on graphon space. J. Comb. Theory A Peter Diao, Dominique Guillot, Apoorva Khare, Bala Rajaratnam
2015	J	`jnl`	Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS). CoRR Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III
2014	J	`jnl`	Detecting the impact area of BP deepwater horizon oil discharge: an analysis by time varying coefficient logistic models and boosted trees. Comput. Stat. Tianxi Li, Chao Gao, Meng Xu, Bala Rajaratnam
2014	—	`conf`	Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. NIPS Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam
2014	J	`jnl`	Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. CoRR Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam
2013	J	`jnl`	A note on the lack of symmetry in the graphical lasso. Comput. Stat. Data Anal. Benjamin T. Rolfs, Bala Rajaratnam
2013	J	`jnl`	Best permutation analysis. J. Multivar. Anal. Bala Rajaratnam, Julia Salzman
2013	A	`conf`	Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension. AISTATS Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III
2013	—	`conf`	Two-stage variable selection for molecular prediction of disease. CAMSAP Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III
2012	J	`jnl`	Hub Discovery in Partial Correlation Graphs. IEEE Trans. Inf. Theory Alfred O. Hero III, Bala Rajaratnam
2012	J	`jnl`	Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation CoRR Dominique Guillot, Bala Rajaratnam, Benjamin T. Rolfs, Arian Maleki, Ian Wong
2012	—	`conf`	Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation. NIPS Benjamin T. Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki
2012	—	`conf`	Natural order recovery for banded covariance models. SAM Benjamin T. Rolfs, Bala Rajaratnam
2012	J	`jnl`	Positive Definite Completion Problems for Bayesian Networks. SIAM J. Matrix Anal. Appl. Emanuel Ben-David, Bala Rajaratnam
2012	J	`jnl`	Successive Standardization of Rectangular Arrays. Algorithms Richard A. Olshen, Bala Rajaratnam
2011	C	`conf`	A local dependence measure and its application to screening for high correlations in large data sets. FUSION Kumar Sricharan, Alfred O. Hero III, Bala Rajaratnam
2011	—	`conf`	Successive Normalization of Rectangular Arrays: Rates of Convergence. CCP Richard A. Olshen, Bala Rajaratnam
2010	J	`jnl`	Learning mixture models via component-wise parameter smoothing. Comput. Stat. Data Anal. Chandan K. Reddy, Bala Rajaratnam
2009	—	`ch.`	Theory and Practice of Expectation Maximization (EM) Algorithm. Encyclopedia of Data Warehousing and Mining Chandan K. Reddy, Bala Rajaratnam
2008	B	`conf`	Component-wise parameter smoothing for learning mixture models. ICPR Chandan K. Reddy, Bala Rajaratnam
2008	J	`jnl`	TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam
2006	A*	`conf`	Stability Region Based Expectation Maximization for Model-based Clustering. ICDM Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratnam