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ETS
2000
IEEE
135views Hardware» more  ETS 2000»
13 years 8 months ago
Results of a telecollaborative activity involving geographically disparate preservice teachers
This article discusses a telecollaborative activity that combines many strategies of interest in teacher education (i.e., case-based learning, online discussion, cross-university ...
Kara M. Dawson, Cheryl L. Mason, Philip Molebash
BDA
2007
13 years 10 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
CVPR
2009
IEEE
15 years 4 months ago
Active Learning for Large Multi-class Problems
Scarcity and infeasibility of human supervision for large scale multi-class classification problems necessitates active learning. Unfortunately, existing active learning methods ...
Prateek Jain (University of Texas at Austin), Ashi...
ICML
2004
IEEE
14 years 2 months ago
Active learning using pre-clustering
The paper is concerned with two-class active learning. While the common approach for collecting data in active learning is to select samples close to the classification boundary,...
Hieu Tat Nguyen, Arnold W. M. Smeulders
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 6 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud