9 citations · 16 across the 8 of their papers we have counts for
8 papers
Sparse Bayesian Learning Algorithms Revisited: From Learning Majorizers to Structured Algorithmic Learning using Neural Networks
Rushabha Balaji, Kuan-Lin Chen, Danijela Cabric +1
Sparse Bayesian Learning is one of the most popular sparse signal recovery methods, and various algorithms exist under the SBL paradigm. However, given a performance metric and a s…
A Comparative Study of Invariance-Aware Loss Functions for Deep Learning-based Gridless Direction-of-Arrival Estimation
Kuan-Lin Chen, Bhaskar D. Rao
Covariance matrix reconstruction has been the most widely used guiding objective in gridless direction-of-arrival (DoA) estimation for sparse linear arrays. Many semidefinite progr…
Subspace Representation Learning for Sparse Linear Arrays to Localize More Sources than Sensors: A Deep Learning Methodology
Kuan-Lin Chen, Bhaskar D. Rao
Localizing more sources than sensors with a sparse linear array (SLA) has long relied on minimizing a distance between two covariance matrices and recent algorithms often utilize s…
A DNN based Normalized Time-frequency Weighted Criterion for Robust Wideband DoA Estimation
Kuan-Lin Chen, Ching-Hua Lee, Bhaskar D. Rao +1
Deep neural networks (DNNs) have greatly benefited direction of arrival (DoA) estimation methods for speech source localization in noisy environments. However, their localization a…
Leveraging Heteroscedastic Uncertainty in Learning Complex Spectral Mapping for Single-channel Speech Enhancement
Kuan-Lin Chen, Daniel D. E. Wong, Ke Tan +3
Most speech enhancement (SE) models learn a point estimate and do not make use of uncertainty estimation in the learning process. In this paper, we show that modeling heteroscedast…
Improved Bounds on Neural Complexity for Representing Piecewise Linear Functions
Kuan-Lin Chen, Harinath Garudadri, Bhaskar D. Rao
A deep neural network using rectified linear units represents a continuous piecewise linear (CPWL) function and vice versa. Recent results in the literature estimated that the numb…
A Generalized Proportionate-Type Normalized Subband Adaptive Filter
Kuan-Lin Chen, Ching-Hua Lee, Bhaskar D. Rao +1
We show that a new design criterion, i.e., the least squares on subband errors regularized by a weighted norm, can be used to generalize the proportionate-type normalized subband a…
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
Kuan-Lin Chen, Ching-Hua Lee, Harinath Garudadri +1
Models recently used in the literature proving residual networks (ResNets) are better than linear predictors are actually different from standard ResNets that have been widely used…