Learning to select learning algorithms
Andre de Carvalho$^{1}$
$^{1}$University of Sao Paulo. São Carlos-SP Brazil
email: andre@icmc.usp.br

Schedule:Thu 22st@14:00, Room: A

A large number of learning algorithms have been developed in the last decades and they have been applied to several tasks in different application domains, with different performance levels. According to empirical and theoretical results, no single algorithm can outperform the others in every task. Thus, when using learning algorithms to solve a new task, we are faced with the question of which algorithm to use. Metalearning provides a general framework for the selection of the most suitable algorithm for a new task. This talk will discuss how metalearning can be used for algorithm selection in different learning tasks.

Short Biography André C. P. L. F. de Carvalho is Full Professor in the department of Computer Science, University of São Paulo, Brazil. His main research interests are data mining, data science and machine learning. Prof. André de Carvalho has more than 300 peer reviewed publications, including 10 best papers awards from conferences organized by ACM, IEEE and SBC. He is a member of the International Association for Statistical Computing (IASC) Council and director of the Center of Machine Learning in Data Analysis of the University of São Paulo.

BibTex

@InProceedings{CLEI-2015:KN-Andre,
	author 		= {Andre de Carvalho},
	title 		= {Learning to select learning algorithms},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI), Special Edition},
	pages 		= {4--4},
	year 		= {2015},
	editor 		= {Universidad Católica San Pablo},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {http://clei.org/clei2015/KN-Andre},
	isbn 		= {978-9972-825-91-0},
	}