Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such models, but usually involves a computationally heavy combinatorial search. Lasso (Tibshirani, 1996) is now being used as a computationally feasible alternative to model selection. Therefore it is important to study La...

The problem of the aggregation of inputs coming from different sources arises in several contexts. Examples are the combination of individual preferences (studied in social choice theory), opinions (judgment aggregation), and data (artificial intelligence). While a number of results are available in each of these disciplines, a question that has been addressed only recently is how similar these...

This paper presents two novel likelihood terms for silhouettes and contours in model-based contexts. Despite the power of such formulations, building likelihoods that truly reflect the good configurations of the problem is by no means easy due to, most commonly, the violation of consistency principle resulting in the introduction of spurious, unrelated peaks/minima that make target localization...

The messenger paradigm is an alternative to computer communication based on the exchange of programs called messengers which are afterwards executed, instead of messages that are interpreted. The communication by messenger paradigm can be used to implement both low level software such as communication protocols and high level software such as distributed applications. Using the messenger paradi...

Adaptive model predictive control is applied to the control of consistency. The process model used for the control is updated on the basis of the operation conditions. The process gain is calculated by the mass balance equations or by using the preceding consistency measurement. The process dynamics is determined on the basis of the scheduling variable, i.e. the flow rate. The performance of th...

Wide-area replicated systems are characterized by a conflict between performance, availability and consistency. As a consequence, “one-size-fits-all” approaches will inadequately address every situation. Therefore, there is a need for a formalism that can be used to express consistency requirements in a uniform way, as well as for new algorithms and techniques appropriate for the wide-area sett...

The memory consistency model supported by a multiprocessor directly affects its performance. Thus, several attempts have been made to relax the consistency models to allow for more buffering and pipelining of memory accesses. Unfortunately, the potential increase in performance afforded by relaxing the consistency model is accompanied by a more complex programming model. This paper introduces t...

Eventual consistency is a more natural model than strong consistency for a distributed system, since it is closer to the underlying physical reality. Therefore, we propose that it is important to find a programming model that is both congenial to developers and supports eventual consistency. In particular, we consider that a crucial test for such a model is that it should support edge computati...

Today’s enterprises are dynamic where many variances of business process models can exist due to several reasons such as: the need to target different customer types, rely on particular IT systems or comply with specific country regulations. Automated maintenance of the consistency between process variants is an important goal that saves the time and efforts of process modelers. In this paper, ...

Sequential consistency is a multiprocessor memory model of both practical and theoretical importance. Unfortunately, the general problem of verifying that a finitestate protocol implements sequential consistency is undecidable, and in practice, validating that a real-world, finitestate protocol implements sequential consistency is very time-consuming and costly. In this work, we show that for m...