A new large margin classifier, named MaxiMin Margin Machine (M4 ) is proposed in this paper. This new classifier is constructed based on both a "local" and a "globa...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
We discuss challenges and opportunities for developing generalized task markets where human and machine intelligence are enlisted to solve problems, based on a consideration of th...
Sparsity is a desirable property in high dimensional learning. The 1-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity. Combining the...
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...
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...