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» Mobile learning: A framework and evaluation
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ICCV
2007
IEEE
14 years 11 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
IUI
1997
ACM
14 years 1 months ago
The Pedagogical Design Studio: Exploiting Artifact-Based Task Models for Constructivist Learning
Intelligentlearning environments that support constructivism shouldprovideactivelearningexperiencesthatarecustomized for individuallearners. To do so, they must determine learner ...
James C. Lester, Patrick J. Fitzgerald, Brian A. S...
ECML
2006
Springer
14 years 26 days 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...
RAS
2010
117views more  RAS 2010»
13 years 7 months ago
Extending BDI plan selection to incorporate learning from experience
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. We describe a novel BDI exe...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
MICCAI
2005
Springer
14 years 10 months ago
Efficient Learning by Combining Confidence-Rated Classifiers to Incorporate Unlabeled Medical Data
Abstract. In this paper, we propose a new dynamic learning framework that requires a small amount of labeled data in the beginning, then incrementally discovers informative unlabel...
Weijun He, Xiaolei Huang, Dimitris N. Metaxas, Xia...