[HTML][HTML] PredMaX: Predictive maintenance with explainable deep convolutional autoencoders
A novel data exploration framework (PredMaX) for predictive maintenance is introduced in
the present paper. PredMaX offers automatic time period clustering and efficient …
the present paper. PredMaX offers automatic time period clustering and efficient …
FedDMC: Efficient and Robust Federated Learning via Detecting Malicious Clients
Federated learning (FL) has gained popularity in the field of machine learning, which allows
multiple participants to collaboratively learn a highly-accurate global model without …
multiple participants to collaboratively learn a highly-accurate global model without …
On the power of SVD in the stochastic block model
A popular heuristic method for improving clustering results is to apply dimensionality
reduction before running clustering algorithms. It has been observed that spectral-based …
reduction before running clustering algorithms. It has been observed that spectral-based …
[HTML][HTML] Transformer network for data imputation in electricity demand data
Load forecasting necessitates a significant amount of smart meter data. Several elements in
this process, including device malfunctions and signal transmission issues, produce missing …
this process, including device malfunctions and signal transmission issues, produce missing …
Confident Clustering via PCA Compression Ratio and Its Application to Single-cell RNA-seq Analysis
Y Li, CS Mukherjee, J Zhang - arXiv preprint arXiv:2205.09849, 2022 - arxiv.org
Unsupervised clustering algorithms for vectors has been widely used in the area of machine
learning. Many applications, including the biological data we studied in this paper, contain …
learning. Many applications, including the biological data we studied in this paper, contain …