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» A Framework for Multiple-Instance Learning
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PAMI
2011
14 years 10 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
AAAI
2011
14 years 3 months ago
Coordinated Multi-Agent Reinforcement Learning in Networked Distributed POMDPs
In many multi-agent applications such as distributed sensor nets, a network of agents act collaboratively under uncertainty and local interactions. Networked Distributed POMDP (ND...
Chongjie Zhang, Victor R. Lesser
CVPR
2012
IEEE
13 years 6 months ago
Learning rotation-aware features: From invariant priors to equivariant descriptors
Identifying suitable image features is a central challenge in computer vision, ranging from representations for lowlevel to high-level vision. Due to the difficulty of this task,...
Uwe Schmidt, Stefan Roth
ISI
2003
Springer
15 years 9 months ago
Authorship Analysis in Cybercrime Investigation
Criminals have been using the Internet to distribute a wide range of illegal materials globally in an anonymous manner, making criminal identity tracing difficult in the cybercrime...
Rong Zheng, Yi Qin, Zan Huang, Hsinchun Chen
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ICML
2005
IEEE
16 years 4 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic