While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Abstract--In this paper, we propose track routing and optimization for yield (TROY), the first track router for the optimization of yield loss due to random defects. As the probabi...
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...
—In this paper, we present a near-lossless compression scheme for scalar-quantized source codec parameters based on iterative source-channel decoding (ISCD). The scheme is compar...
Laurent Schmalen, Peter Vary, Thorsten Clevorn, Ma...
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...