A unified optimization framework with PADMM solver for jointly learning time-varying graphs and imputing missing graph signals, with convergence and statistical guarantees.
Gegenbauer graph neural networks for time-varying signal reconstruc- tion,
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Learning Time-Varying Graphs from Incomplete Graph Signals
A unified optimization framework with PADMM solver for jointly learning time-varying graphs and imputing missing graph signals, with convergence and statistical guarantees.