Conditional independence relations involving latent variables do not necessarily imply observable independences. They may imply inequality constraints on observable parameters and causal bounds, which can be used for falsification and identification. The literature on computing such constraints often involve a deterministic underlying data generating process in a counterfactual framework. If an...

Virtually all known distance-based similarity search indexes make use of some form of numerical constraints (triangle inequality, additive distance bounds, . . . ) on similarity values for pruning and selection. The use of such numerical constraints, however, often leads to large variations in the numbers of objects examined in the execution of a query, making it difficult to control the execut...

In this work, we examine port crane scheduling with spatial and separation constraints. Although common to most port operations, these constraints have not been previously studied. We assume that cranes cannot cross, there is a minimum distance between cranes and jobs cannot be done simultaneously. The objective is to find a crane-to-job matching which maximizes throughput under these constrain...

The description logic PALC allows to express degrees of belief in concept and role assertions for individuals. We are concerned with the mathematical development of a theory for probabilistic ABoxes in PALC. The axioms of probability give us a set of linear constraints on the models of an ABox. Moreover, an independence assumption regarding the assertions for different individuals yields additi...

In a multimodal conversation, user referring patterns could be complex, involving multiple referring expressions from speech utterances and multiple gestures. To resolve those references, multimodal integration based on semantic constraints is insufficient. In this paper, we describe a graph-based probabilistic approach that simultaneously combines both semantic and temporal constraints to achi...

introduction: the critical dependence of healthcare services systems on information along with the indigenous restriction of paper documents in satisfying this need has caused a trend toward computer information systems. the main goal of such systems is to achieve electronic health records (ehr). however, implementation of ehr in healthcare organizations is difficult and complicated. this resea...

We apply multivariate Lagrange interpolation to synthesizing polynomial quantitative loop invariants for probabilistic programs. We reduce the computation of an quantitative loop invariant to solving constraints over program variables and unknown coefficients. Lagrange interpolation allows us to find constraints with less unknown coefficients. Counterexample-guided refinement furthermore genera...

This paper presents a Markov chain based approach for the probabilistic density control of a large number, swarm, of autonomous agents. The proposed approach specifies the time evolution of the probabilistic density distribution by using a Markov chain, which guides the swarm to a desired steady-state distribution, while satisfying the prescribed ergodicity, motion, and safety constraints. This...

For the computational analysis of biological problems-analyzing data, inferring networks and complex models, and estimating model parameters-it is common to use a range of methods based on probabilistic logic constructions, sometimes collectively called machine learning methods. Probabilistic modeling methods such as Bayesian Networks (BN) fall into this class, as do Hierarchical Bayesian Netwo...

Probabilistic optimization design offers tools for making reliable decisions with the consideration of uncertainty associated with design variables/parameters and simulation models. In a probabilistic design, such as reliability-based design and robust design, the design feasibility is formulated probabilistically such that the probability of the constraint satisfaction (reliability) exceeds th...