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PAMI
2006
206views more  PAMI 2006»
13 years 8 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
TIP
2008
142views more  TIP 2008»
13 years 8 months ago
Image Feature Localization by Multiple Hypothesis Testing of Gabor Features
Several novel and particularly successful object and object category detection and recognition methods based on image features, local descriptions of object appearance, have recent...
Jarmo Ilonen, Joni-Kristian Kamarainen, Pekka Paal...
PR
2007
104views more  PR 2007»
13 years 8 months ago
Optimizing resources in model selection for support vector machine
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
Mathias M. Adankon, Mohamed Cheriet
ICDM
2007
IEEE
138views Data Mining» more  ICDM 2007»
14 years 3 months ago
Bandit-Based Algorithms for Budgeted Learning
We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is s...
Kun Deng, Chris Bourke, Stephen D. Scott, Julie Su...
KDD
1998
ACM
120views Data Mining» more  KDD 1998»
14 years 26 days ago
Ranking - Methods for Flexible Evaluation and Efficient Comparison of Classification Performance
We present the notion of Ranking for evaluation of two-class classifiers. Ranking is based on using the ordering information contained in the output of a scoring model, rather tha...
Saharon Rosset