Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
In this paper, we introduce a new nonlinear evolution partial differential equation for sparse deconvolution problems. The proposed PDE has the form of continuity equation that ar...
We consider the problem of extracting the source signals from an under-determined convolutive mixture assuming known mixing filters. State-of-the-art methods operate in the time-fr...
—Escalating system-on-chip design complexity is the design community to raise the level of abstraction beyond register transfer level. Despite the unsuccessful adoptions of early...
Jason Cong, Bin Liu, Stephen Neuendorffer, Juanjo ...