This paper reports some experiments that compare the accuracy and performance of two stochastic parsing systems. The currently popular Collins parser is a shallow parser whose output contains more detailed semanticallyrelevant information than other such parsers. The XLE parser is a deep-parsing system that couples a Lexical Functional Grammar to a loglinear disambiguation component and provide...

Loglinear modeling methods have become quite straightforward to apply to discrete data X. The models for missing data involve minor extensions of hot-deck methods (Little and Rubin 2002). Edits are structural zeros that forbid certain patterns. Winkler (2003) provided the theory for connecting edit with imputation. In this paper, we give methods and algorithms for modeling/edit/imputation under...

Transliteration of given parallel name entities can be formulated as a phrase-based statistical machine translation (SMT) process, via its routine procedure comprising training, optimization and decoding. In this paper, we present our approach to transliterating name entities using the loglinear phrase-based SMT on character sequences. Our proposed work improves the translation by using bidirec...

We consider an environment of a fixed size that can be converted to another use. This conversion can be made in steps, but it is irreversible. The future benefits (per unit) from the original use, and from the alternative use, follow a diffusion process. For a fairly general case, we show that the value function must be the unique (viscosity) solution to the associated Hamilton-Jacobi-Bellman e...

We present a new part-of-speech tagger that demonstrates the following ideas: (i) explicit use of both preceding and following tag contexts via a dependency network representation, (ii) broad use of lexical features, including jointly conditioning on multiple consecutive words, (iii) effective use of priors in conditional loglinear models, and (iv) fine-grained modeling of unknown word features...

We propose a novel approximation of the risky steady state and construct first-order perturbations around it for general class dynamic equilibrium models with time-varying non-Gaussian risk. offer analytical formulas conditions their local existence uniqueness. apply this technique to featuring Campbell-Cochrane habits, recursive preferences, disaster risk, show how proposed represents implicat...

The possible discrepancy between a hypothesized model and the observed data is measured by so called Goodness of Fit Statistics. In order to decide whether the observed discrepancy is substantial, the distributions of these statistics under the hypothesised model are needed to perform a statistical test. Because of the diiculty to compute the exact distributions, just when the sample size is sm...

We study maximum likelihood estimation in log-linear models under conditional Poisson sampling schemes. We derive necessary and sufficient conditions for existence of the maximum likelihood estimator (MLE) of the model parameters and investigate estimability of the natural and mean-value parameters under a nonexistent MLE. Our conditions focus on the role of sampling zeros in the observed table...

Despite much recent progress on accurate semantic role labeling, previous work has largely used independent classifiers, possibly combined with separate label sequence models via Viterbi decoding. This stands in stark contrast to the linguistic observation that a core argument frame is a joint structure, with strong dependencies between arguments. We show how to build a joint model of argument ...