Relational and First-Order Probability Models
First Order Probabilistic Models for Coreference Resolution
... a first-order proba- bilistic model for ...a first- order logic representation can be incorpo- rated into a probabilistic model and scaled ...
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A Relational Logic for Higher-Order Programs
... developed Relational Higher-Order Logic, a new formalism to reason about relational properties of (pure) higher-order programs written in a simply typed λ-calculus with inductive types and ...
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Unit 19: Probability Models
... When a player first comes into the casino, his chance of beating the house is slightly less than 50-50. A smart gambler will come in and bet the maximum he can afford to lose on one roll and walk away either a ...
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Second-order differentiability of probability functions
... ϕ(x) = P (hη, xi ≤ h(x)) (18) with a twice continuously differentiable h : R m → R and a random vector η with a multivariate lognormal distribution, i.e., the component-wise logarithm log η has a multivariate Gaussian ...
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First-Order Fire Effects Models for Land Management: Overview and Issues
... agement. First-order fire effects models, such as those discussed in accompanying papers, are the building blocks of software systems designed for application to landscapes over time scales from days ...
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First-order logic classification models of musical genres based on harmony
... a first-order logic approach to automatically extract genre classification models using har- ...This models are not black boxes: thanks to the ex- pressiveness of first order ...
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First-order asymptotic theory for parametric misspecification tests of Garch models
... 1. INTRODUCTION A great deal of research has been undertaken on modeling volatility clustering in financial and economic time series, in which the generalized autoregressive conditional heteroskedastic (GARCH) model of ...
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Relational Structures and Models for Coreference Resolution
... the first uses Vilain et al’s scoring scheme, but uses perfect mentions, whereas the second uses system mentions, but ignore in the evaluation any mention that is not both in the system and key ...
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Directed Models For Statistical Relational Learning
... Statistical Relational Learning is a new branch of machine learning that aims to model a joint distribution over relational ...data. Relational data consists of different types of objects where each ...
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Macro economy in models for default probability
... Abstract We inspect the question how to adapt to macro-economical variables those probability of default (PD) estimates where Merton’s model as- sumptions cannot be used. The need for this is to obtain trustworthy ...
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Probability of default models of Russian banks
... reasons. First, we focus on constructing probability of default models for Russian ...logit models for each ...the models or rates of correct prediction, but such informa- tion is not ...
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Probability Models and Statistical Methods in Reliability
... 9.3 Proportional hazards Example 9.2 A set of n = 3 light bulbs are placed on test. The first and second bulbs are 100-watt bulbs and the third bulb is a 60-watt bulb. A single (q = 1) covariate z 1 assumes the ...
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Probability Models for Customer-Base Analysis
... Reflecting on the first and third settings, we see that the transactions can only occur at discrete points in time. The conference occurs at a specific point in time, and one either attends or does not attend; if ...
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Imprecise Probability Models for Logistic Regression
... Chapter 1 Introduction 1.1 Motivation Logistic regression is a well known statistical model that has been applied widely in statistical analysis. It is used in applied statistics to analyze binary and multinomial data. ...
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A Convenient Category for Higher-Order Probability Theory
... probabilistic models in machine learning and statistics in a succinct and structured way, it pays to use higher-order programming languages, such as Church [16], Venture [24], or Anglican ...and ...
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First order marginalised transition random effects models with probit link function
... Marginalised models, also known as marginally specified models, have recently become a popular tool for analysis of discrete longitudinal ...these models introduce complex constraint equations and ...
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First-Order Stable Model Semantics and First-Order Loop Formulas
... the first-order stable model semantics and first-order loop formulas, we extend the syntax of logic programs with explicit quantifiers, which may be useful in overcoming some limitations of ...
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A Hybrid Relational Approach for WSD – First Results
... In future work we intend to carry out experi- ments with different settings: (a) combinations of certain KSs; (b) other sample corpora, of different sizes, genres / domains; and (c) different parameters in Aleph ...
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A First Approach to the Multipurpose Relational Database Server
... multipurpose relational database server are ...In order to achieve this, a combination of existing meta-knowledge bases and new data catalog elements is ...
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Iphone Models In Order
... both models? The order number in functionality, all your orders fast and ordering ...to order on the iphone has some of components and beat the iphone models in order numbers will the ...
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