31 citations · 63 across the 13 of their papers we have counts for
16 papers
Multi-Dictionary Learning for Low Rank Sparse Coding
Boya Ma, Abram Magner, Maxwell McNeil +1
Sparse dictionary coding represents signals as linear combinations of a few dictionary atoms. It has been applied to images, time series, graph signals and multi-way spatio-tempora…
Low Rank Multi-Dictionary Selection at Scale
Boya Ma, Maxwell McNeil, Abram Magner +1
The sparse dictionary coding framework represents signals as a linear combination of a few predefined dictionary atoms. It has been employed for images, time series, graph signals…
Multi-Dictionary Tensor Decomposition
Maxwell McNeil, Petko Bogdanov
Tensor decomposition methods are popular tools for analysis of multi-way datasets from social media, healthcare, spatio-temporal domains, and others. Widely adopted models such as…
Unsupervised Instance and Subnetwork Selection for Network Data
Lin Zhang, Nicholas Moskwa, Melinda Larsen +1
Unlike tabular data, features in network data are interconnected within a domain-specific graph. Examples of this setting include gene expression overlaid on a protein interaction…
Temporal Scale Estimation for Oversampled Network Cascades: Theory, Algorithms, and Experiment
Abram Magner, Carolyn Kaminski, Petko Bogdanov
Spreading processes on graphs arise in a host of application domains, from the study of online social networks to viral marketing to epidemiology. Various discrete-time probabilist…
Temporal Graph Signal Decomposition
Maxwell McNeil, Lin Zhang, Petko Bogdanov
Temporal graph signals are multivariate time series with individual components associated with nodes of a fixed graph structure. Data of this kind arises in many domains including…