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» Learning Models for Object Recognition
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ECML
2006
Springer
15 years 5 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
ECAI
2010
Springer
15 years 2 months ago
Learning action effects in partially observable domains
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
Kira Mourão, Ronald P. A. Petrick, Mark Ste...
NIPS
2008
15 years 3 months ago
An Extended Level Method for Efficient Multiple Kernel Learning
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu
CRIWG
2004
15 years 3 months ago
An Integrated Approach for Analysing and Assessing the Performance of Virtual Learning Groups
Collaborative distance learning involves a variety of elements and factors that have to be considered and measured in order to analyse and assess group and individual performance m...
Thanasis Daradoumis, Alejandra Martínez-Mon...
CVPR
2012
IEEE
13 years 4 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann