3 citations · 11 across the 23 of their papers we have counts for
6 papers · 1 filter
An iterative method for classification of binary data
Denali Molitor, Deanna Needell
In today's data driven world, storing, processing, and gleaning insights from large-scale data are major challenges. Data compression is often required in order to store large amou…
Tribracket Modules
Deanna Needell, Sam Nelson, Yingqi Shi
Niebrzydowski tribrackets are ternary operations on sets satisfying conditions obtained from the oriented Reidemeister moves such that the set of tribracket colorings of an oriente…
Hierarchical Classification using Binary Data
Denali Molitor, Deanna Needell
In classification problems, especially those that categorize data into a large number of classes, the classes often naturally follow a hierarchical structure. That is, some classes…
An Approximate Message Passing Framework for Side Information
Anna Ma, You, Zhou +3
Approximate message passing (AMP) methods have gained recent traction in sparse signal recovery. Additional information about the signal, or \emph{side information} (SI), is common…
Analysis of Fast Structured Dictionary Learning
Saiprasad Ravishankar, Anna Ma, Deanna Needell
Sparsity-based models and techniques have been exploited in many signal processing and imaging applications. Data-driven methods based on dictionary and sparsifying transform learn…
Randomized Projection Methods for Linear Systems with Arbitrarily Large Sparse Corruptions
Jamie Haddock, Deanna Needell
In applications like medical imaging, error correction, and sensor networks, one needs to solve large-scale linear systems that may be corrupted by a small number of arbitrarily la…