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

A review of the Yorkshire and Humber regional waste strategy

Managing waste has become a primary issue for regional planners. This article reports on the institutional process underpinning the region’s strategy and the stages in its production. It emphasises that there has been a watering down of the target for household waste production without appropriate explanation

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

Generalized enthalpy model of a high pressure shift freezing process

High-pressure freezing processes are a novel emerging technology in food processing, offering significant improvements to the quality of frozen foods. To be able to simulate plateau times and thermal history under different conditions, in this work we present a generalized enthalpy model of the high-pressure shift freezing process. The model includes the effects of pressure on conservation of enthalpy and incorporates the freezing point depression of non-dilute food samples. In addition the significant heat transfer effects of convection in the pressurizing medium are accounted for by solving the two-dimensional Navier-Stokes equations. We run the model for several numerical tests where the food sample is agar gel, and find good agreement with experimental data from the literature

Trends in long-term prescribing of dependence forming medicines

Using patient-level primary care data to estimate the extent to which antidepressant medicines are prescribed to people continuously for long periods of time. Aim This descriptive research used patient-level primary care data to estimate the extent to which antidepressant medicines are prescribed to people continuously for long periods of time. The study also drew on survey data and data on the number of prescriptions dispensed. Findings - The number of antidepressant prescriptions dispensed each year in England doubled between 2008 and 2018 - Survey data show that the proportion of adults reporting use of antidepressants in the past year increased in the 1990s, and again between 2007 and 2014 - The average length of time that antidepressants are continuously prescribed to people for has increased over time. - Some types of antidepressants (for example, tricyclics and other antidepressants) tend to be prescribed for longer periods than other types (such as SSRIs). - In 2014, one in twelve prescribing periods for tricyclics and other antidepressants lasted for three years or more Methods The analyses in this report are descriptive and show the overall prevalence of long-term prescribing in each year. We used a sample of around 50,000 patients prescribed at least one antidepressant medicine between 2000 and 2017. This was drawn from the Clinical Practice Research Datalink (CPRD). The CPRD contains data about prescriptions issued by GPs (including the length and size of prescription) and characteristics of the patients prescribed to (such as their age, sex, and area where they live). Medicines were grouped for analysis into: tricyclics, selective serotonin reuptake inhibitors (SSRIs), and other ADMs. The length of individual prescriptions and continuous prescribing periods were derived using information on consultation dates, the quantity of tablets prescribed, and the numeric daily dose

Observed Consequences of Presupernova Instability in Very Massive Stars

This chapter concentrates on the deaths of very massive stars, the events leading up to their deaths, and how mass loss affects the resulting death. The previous three chapters emphasized the theory of wind mass loss, eruptions, and core collapse physics, but here we emphasize mainly the observational properties of the resulting death throes. Mass loss through winds, eruptions, and interacting binaries largely determines the wide variety of different types of supernovae that are observed, as well as the circumstellar environments into which the supernova blast waves expand. Connecting these observed properties of the explosions to the initial masses of their progenitor stars is, however, an enduring challenge and is especially difficult for very massive stars. Superluminous supernovae, pair instability supernovae, gamma ray bursts, and "failed" supernovae are all end fates that have been proposed for very massive stars, but the range of initial masses or other conditions leading to each of these (if they actually occur) are still very certain. Extrapolating to infer the role of very massive stars in the early universe is essentially unencumbered by observational constraints and still quite dicey.Comment: 39 pages, 5 figures, to appear as chapter in the book "Very Massive Stars in the Local Universe", ed. J. Vin

Influence of the Third Dimension of Quasi-Two-Dimensional Cuprate Superconductors on Angle-Resolved Photoemission Spectra

Angle-resolved photoemission spectroscopy (ARPES) presents significant simplications in analyzing strictly two-dimensional (2D) materials, but even the most anisotropic physical systems display some residual three-dimensionality. Here we demonstrate how this third dimension manifests itself in ARPES spectra of quasi-2D materials by considering the example of the cuprate Bi$_2$Sr$_2$CaCu$_2$O$_{8}$ (Bi2212). The intercell, interlayer hopping, which is responsible for $k_z$-dispersion of the bands, is found to induce an irreducible broadening to the ARPES lineshapes with a characteristic dependence on the in-plane momentum $k_\parallel$. Our study suggests that ARPES lineshapes can provide a direct spectroscopic window for establishing the existence of coherent c-axis conductivity in a material via the detection of this new broadening mechanism, and bears on the understanding of 2D to 3D crossover and pseudogap and stripe physics in novel materials through ARPES experiments.Comment: 5 pages, 4 figure

Analysis of rolling bearing power loss models for twin screw oil injected compressor

The mechanical losses inside a screw compressor limit the performance of the compressor in terms of efficiency. These losses arise due to relative motion between elements inside the screw compressor. The estimation of mechanical losses predicted in the literature is around 10-15% of the total shaft power. One of the elements which contribute significantly to these losses is rolling element bearings. There are numerous mathematical models available which predict power losses in the rolling bearings. The objective of this paper is to study different models to predict power loss for rolling bearings and to predict the power losses for the bearings used for oil injected, twin screw compressor. A comparison between different power loss models for different operating conditions of compressor is also presented in this paper and results of analysis are compared with available experimental observations. The analysis helps to determine suitable power loss model for different operating conditions and more realistic predictions of the power losses. This allows designers for more accurate estimation of the performance of screw compressors