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KDD
2001
ACM
166views Data Mining» more  KDD 2001»
14 years 8 months ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
13 years 9 months ago
Class-Specific Ensembles for Active Learning
In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
Amit Mandvikar, Huan Liu
CE
2007
102views more  CE 2007»
13 years 7 months ago
ICT and learning: Lessons from Australian classrooms
Research into Information and Communication Technologies (ICT) in schools is well into its third decade but there is still a pressing need to better understand how computer-based ...
Debra N. A. Hayes
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 3 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
CVPR
2005
IEEE
14 years 9 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...