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» Sublinear Optimization for Machine Learning
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ICML
2005
IEEE
14 years 9 months ago
Learning hierarchical multi-category text classification models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Craig Saunders, John Shawe-Taylor, Juho Rousu, S&a...
ML
1998
ACM
153views Machine Learning» more  ML 1998»
13 years 8 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun
ICML
2009
IEEE
14 years 9 months ago
Learning kernels from indefinite similarities
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
Yihua Chen, Maya R. Gupta, Benjamin Recht
CC
2006
Springer
124views System Software» more  CC 2006»
14 years 22 days ago
Hybrid Optimizations: Which Optimization Algorithm to Use?
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
ICML
2008
IEEE
14 years 9 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin