Viterbi Training for PCFGs: Hardness Results and Competitiveness of Uniform Initialization

We consider the search for a maximum likelihood assignment of hidden derivations and grammar weights for a probabilistic context-free grammar, the problem approximately solved by “Viterbi training.” We show that solving and even approximating Viterbi training for PCFGs is NP-hard. We motivate the use of uniformat-random initialization for Viterbi EM as an optimal initializer in absence of further information about the correct model parameters, providing an approximate bound on the log-likelihood.

Empirical Risk Minimization for Probabilistic Grammars: Sample Complexity and Hardness of Learning

Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. They are used ubiquitously in computational linguistics. We present a framework, reminiscent of structural risk minimization, for empirical risk minimization of probabilistic grammars using the log-loss. We derive sample complexity bounds in this framework that apply both to the supervised setting and the unsupervised setting. By making assumptions about the underlying distribution that are appropriate for natural language scenarios, we are able to derive distribution-dependent sample complexity bounds for probabilistic grammars. We also give simple algorithms for carrying out empirical risk minimization using this framework in both the supervised and unsupervised settings. In the unsupervised case, we show that the problem of minimizing empirical risk is NP-hard. We therefore suggest an approximate algorithm, similar to expectation-maximization, to minimize the empirical risk. Learning from data is central to contemporary computational linguistics. It is in common in such learning to estimate a model in a parametric family using the maximum likelihood principle. This principle applies in the supervised case (i.e., using annotate

Boundary-Layer Similar Solutions for Equilibrium Dissociated Air and Application to the Calculation of Laminar Heat-Transfer Distribution on Blunt Bodies in High-Speed Flow

No abstract availabl

Empirical Risk Minimization with Approximations of Probabilistic Grammars

Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. We present a framework, reminiscent of structural risk minimization, for empirical risk minimization of the parameters of a fixed probabilistic grammar using the log-loss. We derive sample complexity bounds in this framework that apply both to the supervised setting and the unsupervised setting.

Joint Morphological and Syntactic Disambiguation

In morphologically rich languages, should morphological and syntactic disambiguation be treated sequentially or as a single problem? We describe several efficient, probabilistically interpretable ways to apply joint inference to morphological and syntactic disambiguation using lattice parsing. Joint inference is shown to compare favorably to pipeline parsing methods across a variety of component models. State-of-the-art performance on Hebrew Treebank parsing is demonstrated using the new method. The benefits of joint inference are modest with the current component models, but appear to increase as components themselves improve

Impact-Melt Populations in Apollo Drive-Tubes

No abstract availabl

First Results of the 74 MHz VLA-Pie Town Link. Hercules A at Low Frequencies

We present the results of the first successful observations of the Pie Town link with the Very Large Array (VLA) at 74 MHz on Hercules A. The improvement in resolution from 25 arcsec to 10 arcsec resolves the helical- and ring-like features seen at higher frequencies. We also present new high dynamic range images of this powerful radio galaxy at 325 MHz. Our low frequency observations confirm the multiple outburst interpretation of the spectral index differences at high frequencies. Comparison between our radio and ROSAT X-ray data does not reveal any association between the X-ray emission from the cluster and the radio lobes. There are no extra regions of radio emission at 74 MHz.Comment: 9 pages, 7 figures, accepted for publication in MNRA

On Markovian solutions to Markov Chain BSDEs

We study (backward) stochastic differential equations with noise coming from a finite state Markov chain. We show that, for the solutions of these equations to be `Markovian', in the sense that they are deterministic functions of the state of the underlying chain, the integrand must be of a specific form. This allows us to connect these equations to coupled systems of ODEs, and hence to give fast numerical methods for the evaluation of Markov-Chain BSDEs

ac Stark shift and multiphoton-like resonances in low-frequency driven optical lattices

We suggest that Bose-Einstein condensates in optical lattices subjected to ac forcing with a smooth envelope may provide detailed experimental access to multiphoton-like transitions between ac-Stark-shifted Bloch bands. Such transitions correspond to resonances described theoretically by avoided quasienergy crossings. We show that the width of such anticrossings can be inferred from measurements involving asymmetric pulses. We also introduce a pulse tracking strategy for locating the particular driving amplitudes for which resonances occur. Our numerical calculations refer to a currently existing experimental set-up [Haller et al., PRL 104, 200403 (2010)].Comment: 5 pages, 6 figure

Hospital implementation of health information technology and quality of care: are they related?

Recently, there has been considerable effort to promote the use of health information technology (HIT) in order to improve health care quality. However, relatively little is known about the extent to which HIT implementation is associated with hospital patient care quality. We undertook this study to determine the association of various HITs with: hospital quality improvement (QI) practices and strategies; adherence to process of care measures; risk-adjusted inpatient mortality; patient satisfaction; and assessment of patient care quality by hospital quality managers and front-line clinicians.This work was supported by a grant from the Commonwealth Fund. We are indebted to Anthony Shih and Anne-Marie Audet of the Fund for their advice, support, and constructive suggestions throughout the design and conduct of the study. We thank our colleagues - Raymond Kang, Peter Kralovec, Sally Holmes, Frances Margolin, and Deborah Bohr - for their valuable contributions to the development of the QAS, the CPS, and the database on which the analytic findings reported here were based. We also thank 3 M (TM) Health Information Systems' for use of its All Patient Refined Diagnosis Related Groups (APR-DRGs) software. We especially wish to thank Jennifer Drake for her contributions not only to survey development, but also to earlier analysis of survey findings relevant to this paper. (Commonwealth Fund)Published versio