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» Spectral Algorithms for Supervised Learning
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ICML
2009
IEEE
15 years 10 months ago
A least squares formulation for a class of generalized eigenvalue problems in machine learning
Many machine learning algorithms can be formulated as a generalized eigenvalue problem. One major limitation of such formulation is that the generalized eigenvalue problem is comp...
Liang Sun, Shuiwang Ji, Jieping Ye
ATAL
2010
Springer
14 years 11 months ago
Learning multirobot joint action plans from simultaneous task execution demonstrations
The central problem of designing intelligent robot systems which learn by demonstrations of desired behaviour has been largely studied within the field of robotics. Numerous archi...
Murilo Fernandes Martins, Yiannis Demiris
ICML
2007
IEEE
15 years 10 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ICML
2001
IEEE
15 years 10 months ago
Bayesian approaches to failure prediction for disk drives
Hard disk drive failures are rare but are often costly. The ability to predict failures is important to consumers, drive manufacturers, and computer system manufacturers alike. In...
Greg Hamerly, Charles Elkan
AI
2006
Springer
15 years 1 months ago
A Classification-Based Glioma Diffusion Model Using MRI Data
Gliomas are diffuse, invasive brain tumors. We propose a 3D classification-based diffusion model, cdm, that predicts how a glioma will grow at a voxel-level, on the basis of featur...
Marianne Morris, Russell Greiner, Jörg Sander...