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» TRUST-TECH based Methods for Optimization and Learning
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134
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ICML
1995
IEEE
16 years 1 months ago
Learning Policies for Partially Observable Environments: Scaling Up
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...
100
Voted
FGR
2008
IEEE
153views Biometrics» more  FGR 2008»
15 years 7 months ago
Facial image analysis using local feature adaptation prior to learning
Many facial image analysis methods rely on learningbased techniques such as Adaboost or SVMs to project classifiers based on the selection of local image filters (e.g., Haar and...
Rogerio Feris, Ying-li Tian, Yun Zhai, Arun Hampap...
102
Voted
CVPR
2005
IEEE
16 years 2 months ago
Unsupervised Learning of Discriminative Edge Measures for Vehicle Matching between Non-Overlapping Cameras
This paper proposes a novel method for matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem: p...
Ying Shan, Harpreet S. Sawhney, Rakesh Kumar
98
Voted
LCN
2005
IEEE
15 years 6 months ago
Automated Traffic Classification and Application Identification using Machine Learning
The dynamic classification and identification of network applications responsible for network traffic flows offers substantial benefits to a number of key areas in IP network engi...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...
107
Voted
ICCV
2009
IEEE
14 years 10 months ago
Group-sensitive multiple kernel learning for object categorization
In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categoriza...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...