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120
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AIEDAM
2004
96views more  AIEDAM 2004»
15 years 3 months ago
Learning while designing
: This paper reports on preliminary results of an explorative study of a protocol analysis of team learning while designing using in-situ data. Two measurement-based frameworks are...
Gourabmoy Nath, John S. Gero
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 8 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
147
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KDD
2010
ACM
247views Data Mining» more  KDD 2010»
15 years 5 months ago
Active learning for biomedical citation screening
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
103
Voted
IROS
2008
IEEE
121views Robotics» more  IROS 2008»
15 years 10 months ago
Learning robot motion control with demonstration and advice-operators
Abstract— As robots become more commonplace within society, the need for tools to enable non-robotics-experts to develop control algorithms, or policies, will increase. Learning ...
Brenna Argall, Brett Browning, Manuela M. Veloso
119
Voted
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
15 years 1 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...