The observed features of a given phenomenon are not all equally informative: some may be
noisy, others correlated or irrelevant. The purpose of feature selection is to select a set of …

Bayesian networks are a formalism for probabilistic reasonning that is more and more used
for classification task in data-mining. In some situations, the network structure is given by an …

In data analysis, latent variables play a central role because they help provide powerful insights
into a wide variety of phenomena, ranging from biological to human sciences. The latent …

Defect inspection in semiconductor processes has become a challenging task due to
continuous shrink of device patterns (pitches less than 32 nm) as we move from node to node. …

For many years traditional 193i lithography has been extended to the next technology node
by means of multi-patterning techniques. However recently such a 193i technology became …

We discuss a decision theoretic approach to learn causal Bayesian networks from
observational data and experiments. We use the information of observational data to learn a …

CD-SEM images inherently contain a significant level of noise. This is because a limited
number of frames are used for averaging, which is critical to ensure throughput and minimize …

On product overlay (OPO) challenges are quickly becoming yield limiters for the latest
technology nodes, requiring new and innovative metrology solutions. In this paper we will cover …

Originally devoted to specific applications such as biology, medicine and demography, duration
models are now widely used in economy, finance or reliability. Recent works in various …

One of the many constrains of High Numerical Aperture Extreme Ultraviolet Lithography (High
NA EUVL) is related to resist thickness. In fact, one of the consequences of moving from …