This is yet another introduction to log-linear (“maximum entropy”) models for NLP practitioners, in the spirit of Berger (1996) and Ratnaparkhi (1997b). The derivations here are similar to Berger’s, but more details are filled in and some errors are corrected. I do not address iterative scaling (Darroch and Ratcliff, 1972), but rather give derivations of the gradient and Hessian of the dual obj...

Bath application of the GABAB receptor agonist baclofen produced a concentration-dependent long-lasting potentiation (LLP) of the evoked population spike in the dentate gyrus of rat hippocampal slices. A high concentration of baclofen (5 microM) also produced a loss of inhibition that was manifested as the appearance of epileptiform, multiple evoked population spikes and a decrease in paired-pu...

Learning from Label Proportions (LLP) is a learning setting, where the training data is provided in groups, or “bags”, and only the proportion of each class in each bag is known. The task is to learn a model to predict the class labels of the individual instances. LLP has broad applications in political science, marketing, healthcare, and computer vision. This work answers the fundamental quest...

PURPOSE Throughout adulthood, Bruch membrane (BrM) accumulates esterified cholesterol (EC) associated with abundant 60- to 80-nm-diameter lipoprotein-like particles (LLP), putative apolipoprotein B (apoB) lipoproteins secreted by the retinal pigment epithelium (RPE). In the present study, neutral lipid, phospholipids, and retinoid components of human BrM-LLP were assayed. METHODS Particles is...

We present a log-linear model that is used for ranking the string realisations produced for given corpus f-structures by a reversible broadcoverage LFG for German and compare its results with the ones achieved by the application of a language model (LM). Like other authors that have developed log-linear models for realisation ranking, we use a hybrid model that uses linguistically motivated lea...

We present and study a simple Call-By-Push-Value lambdacalculus with fix-points and recursive types. We explain its connection with Linear Logic by presenting a denotational interpretation of the language in any model of Linear Logic equipped with a notion of embedding retraction pairs. We consider the particular case of the Scott model of Linear Logic from which we derive an intersection type ...

Log-linear description logics are a family of probabilistic logics integrating various concepts and methods from the areas of knowledge representation and reasoning and statistical relational AI. We define the syntax and semantics of log-linear description logics, describe a convenient representation as sets of first-order formulas, and discuss computational and algorithmic aspects of probabili...

A single ‘best’ model to predict mortality and understand longevity risk exists only in theory. However, our research and tests conducted on four stochastic mortality models reveals the strengths and weaknesses of each model’s predictive capabilities while simultaneously analyzing how parameters can be set to appropriately smooth and massage the input data. However, just being able to model lon...

in many applications the quality of a process or product is best characterized and summarized by a functional relationship between a response variable and one or more explanatory variables. profile monitoring is used to understand and to check the stability of this relationship over time. therefore checking the capability of a profile seems essential. process capability indices have become very...

We deene a notion of polarization in linear logic (LL) coming from the polarities of Jean-Yves Girard's classical sequent calculus LC 4]. This allows us to deene a translation between the two systems. Then we study the application of this polarization constraint to proof-nets for full linear logic described in 7]. This yields an important simpli-cation of the correctness criterion for polarized...