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Bala Rajaratnam
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2020 – today
- 2023
- [j15]Yun Wei, Bala Rajaratnam, Alfred O. Hero III
:
A Unified Framework for Correlation Mining in Ultra-High Dimension. IEEE Trans. Inf. Theory 69(1): 334-382 (2023) - [c11]Han Wu, Jie Yin, Bala Rajaratnam, Jianyuan Guo:
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. ICLR 2023 - 2022
- [i4]Han Wu
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. CoRR abs/2209.01205 (2022)
2010 – 2019
- 2019
- [j14]Kshitij Khare, Sang-Yun Oh
A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data. Mach. Learn. 108(12): 2061-2086 (2019) - 2017
- [j13]Hamed Firouzi
Two-Stage Sampling, Prediction and Adaptive Regression via Correlation Screening. IEEE Trans. Inf. Theory 63(1): 698-714 (2017) - [c10]Alnur Ali, Kshitij Khare, Sang-Yun Oh
Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. AISTATS 2017: 280-288 - 2016
- [j12]Brett Naul, Bala Rajaratnam, Dario Vincenzi:
The role of the isotonizing algorithm in Stein's covariance matrix estimator. Comput. Stat. 31(4): 1453-1476 (2016) - [j11]Dominique Guillot, Apoorva Khare
Critical exponents of graphs. J. Comb. Theory A 139: 30-58 (2016) - [j10]Alfred O. Hero III, Bala Rajaratnam:
Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining. Proc. IEEE 104(1): 93-110 (2016) - [p1]Alfred O. Hero III, Bala Rajaratnam:
Large-scale correlation mining for biomolecular network discovery. Big Data over Networks 2016: 409-436 - 2015
- [j9]Peter Diao, Dominique Guillot, Apoorva Khare
Differential calculus on graphon space. J. Comb. Theory A 133: 183-227 (2015) - [i3]Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III:
Two-stage Sampling, Prediction and Adaptive Regression via Correlation Screening (SPARCS). CoRR abs/1502.06189 (2015) - 2014
- [j8]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): 141-157 (2014) - [c9]Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam:
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. NIPS 2014: 667-675 - [i2]Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam:
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. CoRR abs/1409.3768 (2014) - 2013
- [j7]Benjamin T. Rolfs, Bala Rajaratnam:
A note on the lack of symmetry in the graphical lasso. Comput. Stat. Data Anal. 57(1): 429-434 (2013) - [j6]Bala Rajaratnam, Julia Salzman:
Best permutation analysis. J. Multivar. Anal. 121: 193-223 (2013) - [c8]Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III:
Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension. AISTATS 2013: 274-288 - [c7]Hamed Firouzi, Bala Rajaratnam, Alfred O. Hero III:
Two-stage variable selection for molecular prediction of disease. CAMSAP 2013: 169-172 - 2012
- [j5]Richard A. Olshen, Bala Rajaratnam:
Successive Standardization of Rectangular Arrays. Algorithms 5(1): 98-112 (2012) - [j4]Emanuel Ben-David
Positive Definite Completion Problems for Bayesian Networks. SIAM J. Matrix Anal. Appl. 33(2): 617-638 (2012) - [j3]Alfred O. Hero III, Bala Rajaratnam:
Hub Discovery in Partial Correlation Graphs. IEEE Trans. Inf. Theory 58(9): 6064-6078 (2012) - [c6]Benjamin T. Rolfs, Bala Rajaratnam:
Natural order recovery for banded covariance models. SAM 2012: 365-368 - [c5]Benjamin T. Rolfs, Bala Rajaratnam, Dominique Guillot, Ian Wong, Arian Maleki:
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation. NIPS 2012: 1583-1591 - [i1]Dominique Guillot, Bala Rajaratnam, Benjamin T. Rolfs, Arian Maleki, Ian Wong:
Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation. CoRR abs/1211.2532 (2012) - 2011
- [c4]Richard A. Olshen, Bala Rajaratnam:
Successive Normalization of Rectangular Arrays: Rates of Convergence. CCP 2011: 239-245 - [c3]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: 1-8 - 2010
- [j2]Chandan K. Reddy
Learning mixture models via component-wise parameter smoothing. Comput. Stat. Data Anal. 54(3): 732-749 (2010)
2000 – 2009
- 2009
- [r1]Chandan K. Reddy, Bala Rajaratnam:
Theory and Practice of Expectation Maximization (EM) Algorithm. Encyclopedia of Data Warehousing and Mining 2009: 1966-1973 - 2008
- [j1]Chandan K. Reddy
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models. IEEE Trans. Pattern Anal. Mach. Intell. 30(7): 1146-1157 (2008) - [c2]Chandan K. Reddy, Bala Rajaratnam:
Component-wise parameter smoothing for learning mixture models. ICPR 2008: 1-4 - 2006
- [c1]Chandan K. Reddy
Stability Region Based Expectation Maximization for Model-based Clustering. ICDM 2006: 522-531
Coauthor Index
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