3 papers
cs.LG2019
Compression and Interpretability of Deep Neural Networks via Tucker Tensor Layer: From First Principles to Tensor Valued Back-Propagation
Giuseppe G. Calvi, Ahmad Moniri, Mahmoud Mahfouz +2
This work aims to help resolve the two main stumbling blocks in the application of Deep Neural Networks (DNNs), that is, the exceedingly large number of trainable parameters and th…
eess.SP2018
Tensor Ensemble Learning for Multidimensional Data
Ilia Kisil, Ahmad Moniri, Danilo P. Mandic
In big data applications, classical ensemble learning is typically infeasible on the raw input data and dimensionality reduction techniques are necessary. To this end, novel framew…
eess.SP2018
A Data Analytics Perspective of the Clarke and Related Transforms in Power Grid Analysis
Danilo P. Mandic, Sithan Kanna, Yili Xia +2
Affordable and reliable electric power is fundamental to modern society and economy, with the Smart Grid becoming an increasingly important factor in power generation and distribut…