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AAAI
2010
15 years 7 months ago
Assisting Users with Clustering Tasks by Combining Metric Learning and Classification
Interactive clustering refers to situations in which a human labeler is willing to assist a learning algorithm in automatically clustering items. We present a related but somewhat...
Sumit Basu, Danyel Fisher, Steven M. Drucker, Hao ...
139
Voted
WCE
2007
15 years 6 months ago
Novel Auxiliary Techniques in Clustering
— Clustering is grouping of patterns according to similarity or distance in different perspectives. Various data representations, similarity measurements and organization manners...
Mohammad Taheri, Reza Boostani
ACSC
2010
IEEE
15 years 19 days ago
Measuring visual consistency in 3d rendering systems
One of the major challenges facing a present day game development company is the removal of bugs from such complex virtual environments. This work presents an approach for measuri...
Alfredo Nantes, Ross Brown, Frédéric...
JMLR
2010
230views more  JMLR 2010»
15 years 11 days ago
Learning Dissimilarities for Categorical Symbols
In this paper we learn a dissimilarity measure for categorical data, for effective classification of the data points. Each categorical feature (with values taken from a finite set...
Jierui Xie, Boleslaw K. Szymanski, Mohammed J. Zak...
196
Voted
CVPR
2012
IEEE
13 years 8 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...