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ICML
2004
IEEE
16 years 8 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
ICML
2009
IEEE
16 years 2 months ago
Online learning by ellipsoid method
In this work, we extend the ellipsoid method, which was originally designed for convex optimization, for online learning. The key idea is to approximate by an ellipsoid the classi...
Liu Yang, Rong Jin, Jieping Ye
ICML
2009
IEEE
16 years 2 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
CEC
2007
IEEE
16 years 1 months ago
Parallel learning in heterogeneous multi-robot swarms
Abstract— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques w...
Jim Pugh, Alcherio Martinoli
ICDM
2006
IEEE
182views Data Mining» more  ICDM 2006»
16 years 1 months ago
Active Learning to Maximize Area Under the ROC Curve
In active learning, a machine learning algorithm is given an unlabeled set of examples U, and is allowed to request labels for a relatively small subset of U to use for training. ...
Matt Culver, Kun Deng, Stephen D. Scott