Optimizing weighting factors for a linear combination of terms in a scoring function is a crucial step for success in developing a threading algorithm. Usually weighting factors are optimized to yield the highest success rate on a training dataset, and the determined constant values for the weighting factors are used for any target sequence. Here we explore completely different approaches to ha...

This paper explores a relationship between parameters for the context tree weighting and weights for a general model weighting technique. In particular, an algorithm is proposed that approximately computes the parameters from the weights, and a condition under which no error for the approximation occurs is derived. key words: model weighting technique, tree source, context tree weighting.

Over the past few decades, economists and psychologists have accumulated a large body of experimental evidence on attitudes to risk. This evidence reveals that, when people make decisions under risk, they often depart from the predictions of expected utility. In an effort to capture the experimental data more accurately, researchers have developed a number of so-called nonexpected utility model...