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Found 5 papers, 0 papers with code
A Time-Temperature Dataset for the Strawberry Cold Chain Across Multiple Shipments and Locations
This article describes location aware temperature profiles from six strawberry shipments across the continental United States.
Learning Latent Representations in Neural Networks for Clustering through Pseudo Supervision and Graph-based Activity Regularization
In this paper, we propose a novel unsupervised clustering approach exploiting the hidden information that is indirectly introduced through a pseudo classification objective.
Ranked #1 on
Unsupervised Image Classification
on SVHN
(using extra training data)
GAR: An efficient and scalable Graph-based Activity Regularization for semi-supervised learning
Adjacency of the examples is inferred using the predictions of a neural network model which is first initialized by a supervised pretraining.
Clustering-based Source-aware Assessment of True Robustness for Learning Models
We introduce a novel validation framework to measure the true robustness of learning models for real-world applications by creating source-inclusive and source-exclusive partitions in a dataset via clustering.
Auto-clustering Output Layer: Automatic Learning of Latent Annotations in Neural Networks
As the proposed output layer modification duplicates the softmax nodes at the output layer for each class, GAR allows for competitive learning between these duplicates on a traditional error-correction learning framework to ultimately enable a neural network to learn the latent annotations in this partially supervised setup.
