Matched case-control study designs are commonly implemented in the field of public health. While matching is intended to eliminate confounding, the main potential benefit of matching in case-control studies is a gain in efficiency. Methods for analyzing matched case-control studies have focused on utilizing conditional logistic regression models that provide conditional and not causal estimates...

Increasing exploitation of Instruction Level Parallelism has been the key to high-performance computing in the past few decades. One of the most critical roadblocks to this parallelism is the presence of branches. Branches (both conditional and un-conditional) redirect the stream of instructions resulting in dead cycles in the front-end of the pipeline. In super-pipelined and superscalar archit...

We present a logic for belief revision in which revision of a theory by a sentence is represented using a conditional connective. The conditional is not primitive, but rather defined using two unary modal operators. Our approach captures and extends the classic AGM model without relying on the Limit Assumption. Reasoning about counterfactual or hypothetical situations is also crucial for AI. Ex...

In this paper, we revisit the frequent itemset mining (FIM) problem and focus on studying the pattern growth approach. Existing pattern growth algorithms differ in several dimensions: (1) item search order; (2) conditional database representation; (3) conditional database construction strategy; and (4) tree traversal strategy. They adopted different strategies on these dimensions. Several adapt...

In some situations the number of observations for which y 1⁄4 1 may not be independent. For example, in epidemiological research, case-control studies are widely used in which one or more observed cases are matched with one or more controls. The matching is based on fixed characteristics such as age and sex, and is designed to eliminate the effect of such characteristics in order to more accura...

We propose a scenario based optimization framework for solving the cash flow matching problem where the time horizon of the liabilities is longer than the maturities of available bonds and the interest rates are uncertain. Standard interest rate models can be used for scenarios generation within this framework. The optimal portfolio is found by minimizing the cost at a specific level of shortfa...

This paper, using the covariance information, proposes recursive least-squares (RLS) 4ltering and 4xed-point smoothing algorithms with uncertain observations in linear discrete-time stochastic systems. The observation equation is given by y(k) = (k)Hx(k) + v(k), where { (k)} is a binary switching sequence with conditional probability distribution verifying Eq. (3). This observation equation is ...

Speakers who request information from others often face potential obstacles to getting that information. Their addressees may not know the information, may be unwilling to give it, or may not remember it. In three experiments we show that speakers estimate the greatest potential obstacle to compliance and try to overcome it through their choice of indirect, or conditional, request. I f speakers...

An enormous amount of publications deals with smoothing in the sense of nonparametric regression. However, nearly all of the literature treats the case where predictors and response are related in the form of a function y = m(x) + noise. In many situations this simple functional model does not capture adequately the essential relation between predictor and response. We show by means of speed-fl...

Conditional independence models in the Gaussian case are algebraic varieties in the cone of positive definite covariance matrices. We study these varieties in the case of Bayesian networks, with a view towards generalizing the recursive factorization theorem to situations with hidden variables. In the case when the underlying graph is a tree, we show that the vanishing ideal of the model is gen...