Frequently undesirable outputs are produced together with desirable. This joint production of bad and good outputs in connection with environmental decision models is the subject of this paper. Recently Haynes, Ratick, Bowen and Cummings-Saxton (1993) addressed the same subject matter. They observed that: "... input resources, including the chemicals of concern, produce as joint products the sa...

We introduce the notion of a ‘pure’ Abstract Elementary Class to block trivial counterexamples. We study classes of models of bipartite graphs and show: Main Theorem (cf. Theorem 3.5.2 and Corollary 3.5.6): If 〈λi : i ≤ α < א1〉 is a strictly increasing sequence of characterizable cardinals (Definition 2.1) whose models satisfy JEP(< λ0), there is an Lω1,ω-sentence ψ whose models form a pure AEC...

We describe a method for parameter estimation in bipartite probabilistic graphical models for joint prediction of clinical conditions from the electronic medical record. The method does not rely on the availability of gold-standard labels, but rather uses noisy labels, called anchors, for learning. We provide a likelihood-based objective and a moments-based initialization that are effective at ...

Compressed sensing is an emerging field based on the revelation that a small group of linear projections of a sparse signal contains enough information for reconstruction. In this paper we introduce a new theory for distributed compressed sensing (DCS) that enables new distributed coding algorithms for multi-signal ensembles that exploit both intraand inter-signal correlation structures. The DC...

In recent years, there has been considerable interest in estimating conditional independence graphs in high dimensions. Most previous work has assumed that the variables are multivariate Gaussian, or that the conditional means of the variables are linear; in fact, these two assumptions are nearly equivalent. Unfortunately, if these assumptions are violated, the resulting conditional independenc...

Commutative Jordan algebras are used to express the structure of mixed orthogonal models and to derive complete sufficient statistics. From these statistics, UMVUE, (Uniformly Minimum Variance Unbiased Estimators), are derived for the relevant parameters, first of single models then of several such models. These models may correspond to experiments designed separately so our results may be seen...

This review focuses on animal models used to study certain aspects of 'cementless' joint replacement. Implants used in this application are designed to become attached to the host skeleton through either bone ingrowth into porous surfaces or bone apposition (ongrowth) onto other types of surfaces. Biological fixation of cementless joint replacement implants relies on intramembranous bone regene...

In this work, we introduce several models for grapheme-tophoneme conversion: a conditional maximum entropy model, a joint maximum entropy n-gram model, and a joint maximum entropy n-gram model with syllabification. We examine the relative merits of conditional and joint models for this task, and find that joint models have many advantages. We show that the performance of our best model, the joi...

We present neural network-based joint models for Chinese word segmentation, POS tagging and dependency parsing. Our models are the first neural approaches for fully joint Chinese analysis that is known to prevent the error propagation problem of pipeline models. Although word embeddings play a key role in dependency parsing, they cannot be applied directly to the joint task in the previous work...