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DAGM
2004
Springer
14 years 1 months ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf
IROS
2007
IEEE
150views Robotics» more  IROS 2007»
14 years 2 months ago
Long-Term learning using multiple models for outdoor autonomous robot navigation
Abstract—Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. The navigation task requires identifying safe, traversable pat...
Michael J. Procopio, Jane Mulligan, Gregory Z. Gru...
ICML
2007
IEEE
14 years 8 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...
VLSISP
2010
254views more  VLSISP 2010»
13 years 6 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
SIGKDD
2008
150views more  SIGKDD 2008»
13 years 7 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...