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» A Framework for Multiple-Instance Learning
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2007
152views Robotics» more  RSS 2007»
15 years 5 months ago
Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 6 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
JMLR
2008
116views more  JMLR 2008»
15 years 3 months ago
Support Vector Machinery for Infinite Ensemble Learning
Ensemble learning algorithms such as boosting can achieve better performance by averaging over the predictions of some base hypotheses. Nevertheless, most existing algorithms are ...
Hsuan-Tien Lin, Ling Li
SIGIR
2008
ACM
15 years 3 months ago
Directly optimizing evaluation measures in learning to rank
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma
ICPR
2008
IEEE
15 years 10 months ago
Improving Bayesian Network parameter learning using constraints
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...
Cassio Polpo de Campos, Qiang Ji