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NIPS
2008
13 years 6 months ago
Empirical performance maximization for linear rank statistics
The ROC curve is known to be the golden standard for measuring performance of a test/scoring statistic regarding its capacity of discrimination between two populations in a wide v...
Stéphan Clémençon, Nicolas Va...
IJCNN
2006
IEEE
13 years 10 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang
SAC
2010
ACM
13 years 3 months ago
Optimal linear projections for enhancing desired data statistics
Problems involving high-dimensional data, such as pattern recognition, image analysis, and gene clustering, often require a preliminary step of dimension reduction before or durin...
Evgenia Rubinshtein, Anuj Srivastava
ICMCS
2006
IEEE
192views Multimedia» more  ICMCS 2006»
13 years 10 months ago
Classifier Optimization for Multimedia Semantic Concept Detection
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
Sheng Gao, Qibin Sun
EWCBR
2008
Springer
13 years 6 months ago
Instance-Based Label Ranking using the Mallows Model
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Weiwei Cheng, Eyke Hüllermeier