43 citations · 69 across the 6 of their papers we have counts for
7 papers
Consistent Multiclass Algorithms for Complex Metrics and Constraints
Harikrishna Narasimhan, Harish G. Ramaswamy, Shiv Kumar Tavker +3
We present consistent algorithms for multiclass learning with complex performance metrics and constraints, where the objective and constraints are defined by arbitrary functions of…
Convex Calibrated Surrogates for the Multi-Label F-Measure
Mingyuan Zhang, Harish G. Ramaswamy, Shivani Agarwal
The F-measure is a widely used performance measure for multi-label classification, where multiple labels can be active in an instance simultaneously (e.g. in image tagging, multipl…
Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve
Harikrishna Narasimhan, Shivani Agarwal
The area under the ROC curve (AUC) is a widely used performance measure in machine learning. Increasingly, however, in several applications, ranging from ranking to biometric scree…
Consistent Algorithms for Multiclass Classification with a Reject Option
Harish G. Ramaswamy, Ambuj Tewari, Shivani Agarwal
We consider the problem of -class classification (), where the classifier can choose to abstain from making predictions at a given cost, say, a factor of the cost o…
Consistent Classification Algorithms for Multi-class Non-Decomposable Performance Metrics
Harish G. Ramaswamy, Harikrishna Narasimhan, Shivani Agarwal
We study consistency of learning algorithms for a multi-class performance metric that is a non-decomposable function of the confusion matrix of a classifier and cannot be expressed…
Convex Calibration Dimension for Multiclass Loss Matrices
Harish G. Ramaswamy, Shivani Agarwal
We study consistency properties of surrogate loss functions for general multiclass learning problems, defined by a general multiclass loss matrix. We extend the notion of classific…