Nearest Neighbor search is an important and widely used problem in a number of important application domains. In many of these domains, the dimensionality of the data representati...
A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio ...
Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee,...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...