Extended multi bottom-up tree transducers are de ned and investigated. They are an extension of multi bottom-up tree transducers by arbitrary, not just shallow, left-hand sides of rules; this includes rules that do not consume input. It is shown that such transducers, even linear ones, can compute all transformations that are computed by linear extended top-down tree transducers, which are a th...

Almost every real process exhibits nonlinear behavior in a full operating range. Local Model Networks are networks which are composed of locally accurate models, where output is interpolated by smooth locally active validity functions. This divide-and-conquer strategy is a general way of coping with complex systems. The architecture of LMN benefits from being able to incorporate a priori knowle...

We consider three natural classes of infinite-state HMSCs: globally-cooperative, locally-cooperative and local-choice HMSCs. We show first that model-checking for globally-cooperative and locally-cooperative HMSCs is of the same complexity as for the class of finite state HMSCs. Surprisingly, model-checking local-choice HMSCs turns out to be exponentially more efficient in space than for locall...

We propose semantic role features for a Tree-to-String transducer to model the reordering/deletion of source-side semantic roles. These semantic features, as well as the Tree-to-String templates, are trained based on a conditional log-linear model and are shown to significantly outperform systems trained based on Max-Likelihood and EM. We also show significant improvement in sentence fluency by...

Individual-tree height models were developed for dipterocarpaceae and nondiptoracarpaceaetree family for semi-evergreen forest in Seam Reap, Cambodia. Tree variables data were collected from long term permanent sample plots for all species. The models were first fitted using multiple linear regressions since it is the most commonly used statistical method in forest modeling. The models then wer...