Dimensionality reduction is the problem of finding a low-dimensional representation of highdimensional input data. This paper examines the case where additional information is kno...
—1 In this paper we present a stochastic model order reduction technique for interconnect extraction in the presence of process variabilities, i.e. variation-aware extraction. It...
We consider feature extraction (dimensionality reduction) for compositional data, where the data vectors are constrained to be positive and constant-sum. In real-world problems, t...
Abstract. In this paper, we address the problem of opinion analysis using a probabilistic approach to the underlying structure of different types of opinions or sentiments around ...
The problem of appearance-based recognition of faces and facial expressions is addressed. Previous work on sliced inverse regression (SIR) resulted in the formulation of an appear...
Yangrong Ling, Suchendra M. Bhandarkar, Xiangrong ...