Semi-Supervised Structuring of Complex Data

Rizoiu, Marian-Andrei

Semi-Supervised Structuring of Complex Data

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Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 3239-3239.

Abstract

The objective of the thesis is to explore how complex data can be treated using unsupervised machine learning techniques, in which additional information is injected to guide the exploratory process. Starting from specific problems, our contributions take into account the different dimensions of the complex data: their nature (image, text), the additional information attached to the data (labels, structure, concept ontologies) and the temporal dimension. A special attention is given to data representation and how additional information can be leveraged to improve this representation.

Marian-Andrei Rizoiu. 2013. Semi-Supervised Structuring of Complex Data. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13. IJCAI, 3239–3239. https://ijcai.org/proceedings/2013/506

@inproceedings{ijcai2013p506,
  title     = {Semi-Supervised Structuring of Complex Data},
  author    = {Rizoiu, Marian-Andrei},
  booktitle = {Proceedings of the Twenty-Third International Joint Conference on
               Artificial Intelligence, {IJCAI-13}},
  publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
  editor    = {Francesca Rossi},
  pages     = {3239--3239},
  year      = {2013},
  month     = {8},
  url       = {https://ijcai.org/proceedings/2013/506},
}

TY  - CPAPER
TI  - Semi-Supervised Structuring of Complex Data
AU  - Rizoiu, Marian-Andrei
T2  - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13
PB  - AAAI Press / International Joint Conferences on Artificial Intelligence
PY  - 2013
SP  - 3239
EP  - 3239
UR  - https://ijcai.org/proceedings/2013/506
ER  -