In this paper, we present an algorithm to lay out a particular class of graphs coming from real case studies: the quasi-tree graph class. Protein and internet mappings projects ha...
Chip design in the nanometer regime is becoming increasingly difficult due to process variations. ASIC designers have adopted statistical optimization techniques to mitigate the e...
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
We study the viability of different robust optimization approaches to multiperiod portfolio selection. Robust optimization models treat future asset returns as uncertain coefficie...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...