Adaptive divided difference filtering for simultaneous state and parameter estimation. - Niranjan A. Subrahmanya; Yung C. Shin (Autom., 2009)

Constructive training of recurrent neural networks using hybrid optimization. - Niranjan A. Subrahmanya; Yung C. Shin (Neurocomputing, 2010)

Sparse Multiple Kernel Learning for Signal Processing Applications. - Niranjan A. Subrahmanya; Yung C. Shin (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Granger Causality for Time-Series Anomaly Detection. - Huida Qiu; Yan Liu 002; Niranjan A. Subrahmanya; Weichang Li (ICDM, 2012)

Online subspace and sparse filtering for target tracking in reverberant environment. - Weichang Li; Niranjan A. Subrahmanya; Feng Xu (SAM, 2012)

Identification of Recurrent Patterns in the Activation of Brain Networks. - Firdaus Janoos; Weichang Li; Niranjan A. Subrahmanya; István Ákos Mórocz; William M. Wells III (NIPS, 2012)

A data-based framework for fault detection and diagnostics of non-linear systems with partial state measurement. - Niranjan A. Subrahmanya; Yung C. Shin (Eng. Appl. Artif. Intell., 2013)

A variational Bayesian framework for group feature selection. - Niranjan A. Subrahmanya; Yung C. Shin (Int. J. Mach. Learn. Cybern., 2013)

Cold Start Approach for Data-Driven Fault Detection. - Mihajlo Grbovic; Weichang Li; Niranjan A. Subrahmanya; Adam K. Usadi; Slobodan Vucetic (IEEE Trans. Ind. Informatics, 2013)

Multi-scale Graphical Models for Spatio-Temporal Processes. - Firdaus Janoos; Huseyin Denli; Niranjan A. Subrahmanya (NIPS, 2014)