Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational data...
K-Nearest Neighbor is used broadly in text classification, but it has one deficiency—computational efficiency. In this paper, we propose a heuristic search way to find out the k ...
Chuanyao Yang, Yuqin Li, Chenghong Zhang, Yunfa Hu
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...
We present an efficient analog synthesis algorithm employing regression models of circuit matrices. Circuit matrix models achieve accurate and speedy synthesis of analog circuits...
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed fro...
Claudio Varini, Andreas Degenhard, Tim W. Nattkemp...