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ICML
2002
IEEE
14 years 8 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 2 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
ISDA
2009
IEEE
14 years 2 months ago
Evaluation Measures for Ordinal Regression
—Ordinal regression (OR – also known as ordinal classification) has received increasing attention in recent times, due to its importance in IR applications such as learning to...
Stefano Baccianella, Andrea Esuli, Fabrizio Sebast...
ICRA
2003
IEEE
165views Robotics» more  ICRA 2003»
14 years 19 days ago
Multi-robot task-allocation through vacancy chains
Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumptio...
Torbjørn S. Dahl, Maja J. Mataric, Gaurav S...
IJCAI
2007
13 years 8 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell