From Anderson Rocha on Linkedin:
How can we solve a #classification problem #WithoutLabels ? Check out the latest result of our Artificial intelligence Lab., Recod.ai ( http://Recod.ai ).
General self-supervised learning methods fail to learn discriminative features when classes have closer semantics. They are also often devised for specific modalities.
We propose a strategy to tackle this problem and enable learning from unlabeled data (from different modalities) even when samples from different classes are not prominently diverse. We leverage a novel #EnsembleBasedClustering strategy where clusters derived from different configurations are combined to generate a better grouping for the data samples in a #FullyUnsupervised way and without hyper-parameter tuning.
Check out our work “Reasoning for Complex Data through Ensemble-based Self-Supervised Learning” on ArXiv: https://lnkd.in/emZf34tK 🙂
This is joint work with Gabriel Bertocco , Antonio Theophilo and Fernanda Andalo, Ph.D. !
#ai #ml #deeplearning #selfsupervised #reid #authorshipattribution #recodai #unicamp #artificialintelligence #data
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