11 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
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…
DSL: Discriminative Subgraph Learning via Sparse Self-Representation
Lin Zhang, Petko Bogdanov
The goal in network state prediction (NSP) is to classify the global state (label) associated with features embedded in a graph. This graph structure encoding feature relationships…