Large-scale process fluctuations (particularly random device mismatches) at nanoscale technologies bring about highdimensional strongly nonlinear performance variations that canno...
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Acoustic echoes represent a major source of discomfort in hands free, full-duplex, communication systems. The problem becomes particularly difficult when the loudspeakers are nonl...
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...
State-of-the-art integral-equation-based solvers rely on techniques that can perform a matrix-vector multiplication in O(N) complexity. In this work, a fast inverse of linear comp...