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Found 6 papers, 0 papers with code
On the Sum of Random Samples with Bounded Pareto Distribution
Heavy-tailed random samples, as well as their sum or average, are encountered in a number of signal processing applications in radar, communications, finance, and natural sciences.
Resource Aware Multifidelity Active Learning for Efficient Optimization
Traditional methods for black box optimization require a considerable number of evaluations which can be time consuming, unpractical, and often unfeasible for many engineering applications that rely on accurate representations and expensive models to evaluate.
A Time-Vertex Signal Processing Framework
An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph.
Multilinear Low-Rank Tensors on Graphs & Applications
We propose a new framework for the analysis of low-rank tensors which lies at the intersection of spectral graph theory and signal processing.
Towards stationary time-vertex signal processing
Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor networks.
Tracking Time-Vertex Propagation using Dynamic Graph Wavelets
Graph Signal Processing generalizes classical signal processing to signal or data indexed by the vertices of a weighted graph.
