198 citations · 572 across the 15 of their papers we have counts for
4 papers · 1 filter
Randomized Block Frank-Wolfe for Convergent Large-Scale Learning
Liang Zhang, Gang Wang, Daniel Romero +1
Owing to their low-complexity iterations, Frank-Wolfe (FW) solvers are well suited for various large-scale learning tasks. When block-separable constraints are present, randomized…
Kernel-based Reconstruction of Space-time Functions on Dynamic Graphs
Daniel Romero, Vassilis N. Ioannidis, Georgios B. Giannakis
Graph-based methods pervade the inference toolkits of numerous disciplines including sociology, biology, neuroscience, physics, chemistry, and engineering. A challenging problem en…
Learning Power Spectrum Maps from Quantized Power Measurements
Daniel Romero, Seung-Jun Kim, Georgios B. Giannakis +1
Power spectral density (PSD) maps providing the distribution of RF power across space and frequency are constructed using power measurements collected by a network of low-cost sens…
Kernel-based Reconstruction of Graph Signals
Daniel Romero, Meng Ma, Georgios B. Giannakis
A number of applications in engineering, social sciences, physics, and biology involve inference over networks. In this context, graph signals are widely encountered as descriptors…