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Found 7 papers, 2 papers with code
Kernel KMeans clustering splits for end-to-end unsupervised decision trees
Trees are convenient models for obtaining explainable predictions on relatively small datasets.
Mind the map! Accounting for existing map information when estimating online HDMaps from sensor
While HDMaps are a crucial component of autonomous driving, they are expensive to acquire and maintain.
Generalised Mutual Information: a Framework for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved the Mutual Information (MI) as an unsupervised objective for training neural networks with increasing regularisations.
Sparse GEMINI for Joint Discriminative Clustering and Feature Selection
Feature selection in clustering is a hard task which involves simultaneously the discovery of relevant clusters as well as relevant variables with respect to these clusters.
A Multi-stage deep architecture for summary generation of soccer videos
The results show that our method can detect the actions of the match, identify which of these actions should belong to the summary and then propose multiple candidate summaries which are similar enough but with relevant variability to provide different options to the final editor.
Knowledge-driven Active Learning
The deployment of Deep Learning (DL) models is still precluded in those contexts where the amount of supervised data is limited.
From text saliency to linguistic objects: learning linguistic interpretable markers with a multi-channels convolutional architecture
A lot of effort is currently made to provide methods to analyze and understand deep neural network impressive performances for tasks such as image or text classification.
