Patent ID: 8873843
Filing Date: 2014-10-28
Classification: G06K

Abstract:
1. A nearest-neighbor-based distance metric learning process implemented by a computer, comprising: applying an exponential-based loss function to provide a smooth objective; and determining an objective and a gradient of both hinge-based and exponential-based loss function in a quadratic time of the number of instances using a computer; wherein the loss function and its gradient comprises: where d is distance, x and y are data points, z is sampled from a class which x does not belong to, Z if v in the same class of x, w x,v is if v is not in the same class as x, X is an p×N matrix whose j-th column is the feature vector of x j , W is an N×N matrix whose i,j-th element is w x ,x , S is an N×N diagonal matrix whose i-th diagonal element is Σ j (w ij +w ji ), NN x+ is the size of class of x, N x− is the size of data not in the class of x, and E is the expection over values x,y ˜x .