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PAMI
2011
13 years 4 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
ICASSP
2009
IEEE
14 years 3 months ago
Fingerprint matching based on distance metric learning
This paper considers a method for learning a distance metric in a fingerprinting system which identifies a query content by measuring the distance between the fingerprint of th...
Dalwon Jang, Chang D. Yoo
ICRA
2006
IEEE
110views Robotics» more  ICRA 2006»
14 years 3 months ago
Transfer of Learning for Complex Task Domains: a Demonstration using Multiple Robots
— This paper demonstrates a learning mechanism for complex tasks. Such tasks may be inherently expensive to learn in terms of training time and/or cost of obtaining each training...
Sameer Singh, Julie A. Adams
DAGSTUHL
2009
13 years 10 months ago
Learning Highly Structured Manifolds: Harnessing the Power of SOMs
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Erzsébet Merényi, Kadim Tasdemir, Li...
MLDM
2005
Springer
14 years 2 months ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...