Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Abstract. Visual data
ow environments are ideally suited for modeling digital signal processing (DSP) systems, as many DSP algorithms are most naturally specied by signal
ow gra...
James Hwang, Brent Milne, Nabeel Shirazi, Jeffrey ...
This work investigates how stochastic sampling jitter noise affects the result of system identification, and proposes a modification of known approaches to mitigate the effects of...
—In this paper, a neural network solution to extract independent components from nonlinearly mixed signals is proposed. Firstly, a structurally constrained mixing model is introd...
Pei Gao, Li Chin Khor, Wai Lok Woo, Satnam Singh D...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...