Collaborative optimization problems can often be modeled as a linear program whose objective function and constraints combine data from several parties. However, important applicat...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Recently a deterministic built-in self-test scheme has been presented based on reseeding of multiple-polynomial linear feedback shift registers. This scheme encodes deterministic ...
As practical pattern classification tasks are often very-large scale and serious imbalance such as patent classification, using traditional pattern classification techniques in ...
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...