{"type":"ScholarlyArticle","title":"Graph Construction for Semi-Supervised Learning","authors":[{"name":"Lilian Berton","slug":"lilian-berton","given":"Lilian","family":"Berton","affiliation":""},{"name":"Alneu de Andrade Lopes","slug":"alneu-de-andrade-lopes","given":"Alneu de Andrade","family":"Lopes","affiliation":""}],"abstract":"Semi-Supervised Learning (SSL) techniques have become very relevant since they require a small set of labeled data. In this scenario, graph-based SSL algorithms provide a powerful framework for modeling manifold structures in high-dimensional spaces and are effective for the propagation of the few initial labels present in training data through the graph. An important step in graph-based SSL methods is the conversion of tabular data into a weighted graph. The graph construction has a key role in the quality of the classification in graph-based methods. Nevertheless, most of the SSL literature focuses on developing label inference algorithms without studying graph construction methods and its effect on the base algorithm performance. This PhD project aims to study this issue and proposes new methods for graph construction from ï¬≠at data and improves the performance of the graph-based algorithms.","doi":null,"url":"https://ijcai.org/proceedings/2015/619","pdf":"https://ijcai.org/proceedings/2015/0619.pdf","markdown":"https://ijcai.org/proceedings/2015/619.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/619","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":619,"pages":{"first":4343,"last":4343},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}