Seminar za veštačku inteligenciju, 19. april 2023.

Naredni sastanak Seminara biće održan onlajn u sredu, 19. aprila 2023, sa početkom u 19 časova.
Predavač: Joao Paulo Carvalho, INESC-ID/Instituto Superior Técnico, Universidade de Lisboa, Portugal
Apstrakt: Fuzzy Fingerprints (FFP) are a frequency-based compact classification technique inspired by human fingerprints. They usually perform and compare well against other machine learning techniques when the number of classes is very large. FFPs have been used and adapted for tasks such as mobile phone user identification, web user identification, text authorship attribution, Tweet Topic Detection, prediction of Intensive Care Unit readmissions from medical text notes, Memory-based Collaborative filtering solutions in the Recommendation Systems domain, or cyberbullying detection in social networks.

FFPs have been successfully used as an interpretable text classification technique, but, like most other techniques, have lately been largely surpassed in performance by Large Pre-trained Language Models (LLM), such as BERT or RoBERTa. However, these LLM suffer from the lack of interpretability and explainability. Recently we were able to combine the interpretability and compact characteristics of the FFP framework with the robustness of the large pre-trained models and shown that, even with a small FFP size, this new architecture can generalize and compete with the results from fine-tuned LLM models.
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