1 code implementation • arXiv 2020 • Jorge Piazentin Ono, Sonia Castelo, Roque Lopez, Enrico Bertini, Juliana Freire, Claudio Silva
In recent years, a wide variety of automated machine learning (AutoML) methods have been proposed to search and generate end-to-end learning pipelines.
Human-Computer Interaction
1 code implementation • 2 May 2019 • Sonia Castelo, Thais Almeida, Anas Elghafari, Aécio Santos, Kien Pham, Eduardo Nakamura, Juliana Freire
Fake news and misinformation have been increasingly used to manipulate popular opinion and influence political processes.
no code implementations • 5 Jul 2019 • Aécio Santos, Sonia Castelo, Cristian Felix, Jorge Piazentin Ono, Bowen Yu, Sungsoo Hong, Cláudio T. Silva, Enrico Bertini, Juliana Freire
In this paper, we present Visus, a system designed to support the model building process and curation of ML data processing pipelines generated by AutoML systems.
no code implementations • 14 Dec 2020 • Sonia Castelo, Moacir Ponti, Rosane Minghim
Multiple-instance learning (MIL) is a paradigm of machine learning that aims to classify a set (bag) of objects (instances), assigning labels only to the bags.
no code implementations • 10 Feb 2021 • Sonia Castelo, Rémi Rampin, Aécio Santos, Aline Bessa, Fernando Chirigati, Juliana Freire
The large volumes of structured data currently available, from Web tables to open-data portals and enterprise data, open up new opportunities for progress in answering many important scientific, societal, and business questions.
no code implementations • 29 Feb 2024 • Guande Wu, Jing Qian, Sonia Castelo, Shaoyu Chen, Joao Rulff, Claudio Silva
Text presented in augmented reality provides in-situ, real-time information for users.