This article discusses a rule-based fuzzy model for the identiication of nonlinear MISO (multiple input, single output) systems. The diss cussed method of fuzzy modeling consists of two parts: structure modeling, i.e. determing the numm ber of rules and input variables involved respecc tively, and parameter optimization, i.e. optimizing the location and form of the curves which describe the fuz...

This work develops a fully decentralized variance-reduced learning algorithm foron-device intelligence where nodes store and process the data locally and are onlyallowed to communicate with their immediate neighbors. In the proposed algo-rithm, there is no need for a central or master unit while the objective is to enablethe dispersed nodes to learn the exact global model de...

Bayes nets are relatively recent innovations. As a result, most of their theoretical devel­ opment has focused on the simplest class of single-author models. The introduction of more sophisticated multiple-author set­ tings raises a variety of interesting ques­ tions. One such question involves the na­ ture of compromise and consensus. Poste­ rior compromises let each model process all data to ...

Most algorithms for propagating evidence through belief networks have been exact and exhaustive: they produce an exact (point­ valued) marginal probability for every node in the· network. Often, however, an appli­ cation will not need information about ev­ ery node in the network nor will it need ex­ act probabilities. We present the localized partial evaluation (LPE) propagation algo­ rithm, w...

To evaluate the performance of a real valued ge netic algorithm GA exploiting domain knowledge we sys tematically evaluate the e ect of exogenous parameters us ing analysis of variance The GA platform used for this study is Genocop III a real valued co evolutionary algo rithm implementation for numerical optimization We use the protein structure prediction PSP problem as our test domain Nearly ...

In this paper we design a nonadaptive NC checker for permutation group intersec tion sharpening a result from Blum and Kannan This is a consequence of two results First we show that a nontrivial permutation in the intersection of two given permutation groups described by lists of generators can be computed by an NC algo rithm with one round of parallel queries to the Group Intersection problem ...

Many existing rule learning systems are computationally expensive on large noisy datasets In this paper we evaluate the recently proposed rule learning algorithm IREP on a large and diverse collection of benchmark problems We show that while IREP is extremely e cient it frequently gives error rates higher than those of C and C rules We then propose a num ber of modi cations resulting in an algo...

Recently, data abstraction has been studied in thecontext of separation logic, with noticeable practicalsuccesses: the developed logics have enabled cleanproofs of tricky challenging programs, such as subject-observer patterns, and they have become the basis of ef-ficient verification tools for Java (jStar), C (VeriFast)and Hoare Type Theory (Ynot). In this paper, we giv...

Amorphous computing is the study of programming ultra scale computing environments of smart sensors and actuators that communicate locally via wireless broadcast In such environments where individual el ements have limited resources aggregation into groups is useful for specialization fault tolerance and re source allocation This paper presents a new algo rithm called clubs that takes advantage...

The input output automaton model has recently been de ned in LT LT as a tool for modeling concurrent and distributed discrete event systems of the sorts arising in computer science Since its introduction the model has been used for describing and reasoning about several di erent types of systems including network resource allocation algorithms communication algorithms concurrent database system...