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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
15 years 4 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
EMNLP
2010
15 years 2 months ago
Negative Training Data Can be Harmful to Text Classification
This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Tradit...
Xiaoli Li, Bing Liu, See-Kiong Ng
IPPS
2010
IEEE
15 years 2 months ago
Offline library adaptation using automatically generated heuristics
Automatic tuning has emerged as a solution to provide high-performance libraries for fast changing, increasingly complex computer architectures. We distinguish offline adaptation (...
Frédéric de Mesmay, Yevgen Voronenko...
IGARSS
2010
14 years 11 months ago
Calibrating probabilities for hyperspectral classification of rock types
This paper investigates the performance of machine learning methods for classifying rock types from hyperspectral data. The main objective is to test the impact on classification ...
Sildomar T. Monteiro, Richard J. Murphy
WMTE
2005
IEEE
15 years 10 months ago
Supporting Pervasive Learning Environments: Adaptability and Context Awareness in Mobile Learning
In the mobile learning context, it is helpful to consider context awareness and adaptivity as two sides of the same coin. The purpose of the adaptivity and context awareness is to...
Antti Syvänen, Russell Beale, Mike Sharples, ...