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ICML
2008
IEEE
14 years 8 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
ECML
2006
Springer
13 years 11 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
ICIP
2007
IEEE
14 years 9 months ago
Extrapolating Learned Manifolds for Human Activity Recognition
The problem of human activity recognition via visual stimuli can be approached using manifold learning, since the silhouette (binary) images of a person undergoing a smooth motion...
Tat-Jun Chin, Liang Wang, Konrad Schindler, David ...
HRI
2010
ACM
14 years 1 months ago
Transparent active learning for robots
—This research aims to enable robots to learn from human teachers. Motivated by human social learning, we believe that a transparent learning process can help guide the human tea...
Crystal Chao, Maya Cakmak, Andrea Lockerd Thomaz