Search Results for author:
Found 7 papers, 1 papers with code
Electrical Grid Anomaly Detection via Tensor Decomposition
We showcase that the use of statistical behavior analysis of SCADA communication with tensor decomposition improves the specificity and accuracy of identifying anomalies in electrical grid systems.
Robust Adversarial Defense by Tensor Factorization
This study underscores the potential of integrating tensorization and low-rank decomposition as a robust defense against adversarial attacks in machine learning.
Process Modeling, Hidden Markov Models, and Non-negative Tensor Factorization with Model Selection
Process monitoring allows users to gauge the involvement of an organization in an industrial process or predict the degradation or aging of machine parts in processes taking place at a remote location.
Distributed Out-of-Memory NMF on CPU/GPU Architectures
In this work, we extend NMFk by adding support for dense and sparse matrix operation on multi-node, multi-GPU systems.
Boolean Matrix Factorization via Nonnegative Auxiliary Optimization
Instead of solving the BMF problem directly, this approach solves a nonnegative optimization problem with the constraint over an auxiliary matrix whose Boolean structure is identical to the initial Boolean data.
Distributed Non-Negative Tensor Train Decomposition
Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors.
Coarse-Grain Cluster Analysis of Tensors with Application to Climate Biome Identification
We are particularly interested in understanding how scale effects clustering of the Earth's climate system.
