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ALT
2007
Springer
16 years 1 months ago
Learning Kernel Perceptrons on Noisy Data Using Random Projections
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
Guillaume Stempfel, Liva Ralaivola
SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
15 years 5 months ago
Active Learning with Model Selection in Linear Regression
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
NIPS
2007
15 years 5 months ago
Discriminative Batch Mode Active Learning
Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning...
Yuhong Guo, Dale Schuurmans
AAMAS
2005
Springer
15 years 9 months ago
Towards Time Management Adaptability in Multi-agent Systems
Abstract. So far, the main focus of research on adaptability in multiagent systems (MASs) has been on the agents’ behavior, for example on developing new learning techniques and ...
Alexander Helleboogh, Tom Holvoet, Danny Weyns, Yo...
ICDM
2002
IEEE
70views Data Mining» more  ICDM 2002»
15 years 9 months ago
Progressive Modeling
Presently, inductive learning is still performed in a frustrating batch process. The user has little interaction with the system and no control over the final accuracy and traini...
Wei Fan, Haixun Wang, Philip S. Yu, Shaw-hwa Lo, S...