Natural language queries provide a natural means for common people to interact with computers and access to on-line information. Due to the complexity of natural language, the traditional way of using a single grammar for a single language parser leads to an inefficient, fragile, and often very large language processing system. Multi-Parser Architecture (MPA) intends to alleviate these problems...

We consider the change-point detection problem of deciding, based on noisy measurements, whether an unknown signal over a given graph is constant or is instead piecewise constant over two induced subgraphs of relatively low cut size. We analyze the corresponding generalized likelihood ratio (GLR) statistic and relate it to the problem of finding a sparsest cut in a graph. We develop a tractable...

Recently, monitoring the process mean and variability simultaneously for multivariate processes by using a single control chart has drawn some attention. However, due to the complexity of multivariate distribution, the existing methods in the univariate processes can not be readily extended to the multivariate processes. In this paper, we propose a new single control chart which integrates the ...

The C. elegans polymodal ASH sensory neurons detect mechanical, osmotic, and chemical stimuli and release glutamate to signal avoidance responses. To investigate the mechanisms of this polymodal signaling, we have characterized the role of postsynaptic glutamate receptors in mediating the response to these distinct stimuli. By studying the behavioral and electrophysiological properties of worms...

The Cox proportional hazards model is the standard tool for relative risk estimation and inference for survival studies. The generalized logrank (GLR) approach (Mehrotra and Roth, 2001) has been proposed as a more efficient alternative to the Cox model when the number of subjects is small and there are no ties in the data. However, ties will result if continuous data are grouped by rounding to ...

This paper presents a new statistical language model for speech recognition, based on Generalized LR parsing. The proposed model, the Abstracted Probabilistic GLR (APGLR) model, is an extension of the existing structured language model known as the Probabilistic GLR (PGLR) model. It can predict next words from arbitrarily abstracted categories. The APGLR model is also a generalization of the or...

Motivated by applications in bio and syndromic surveillance, this article is concerned with the problem of detecting a change in the mean of Poisson distributions after taking into account the effects of population size. The family of generalized likelihood ratio (GLR) schemes is proposed and its asymptotic optimality properties are established under the classical asymptotic setting. However, n...

Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Abstract This paper describes a real time visual target tracking using th...

The development of a parser for a Norwegian text-to-speech system is reported. The Generalized Left Right (GLR) algorithm [1] is applied, which is a generalization of the well known LR algorithm for parsing computer languages. This paper describes briefly the GLR algorithm, the integration of a probabilistic scoring model, our implementation of the parser in C++, attribute structures, lexical i...