We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leible...

Consistency of models and model transformations are strongly interrelated topics. It is thus desirable to have a single notation to express model properties concerning both aspects. When using meta modeling techniques, graph transformations are a natural candidate to express model transformations. This paper explores the use of graph transformations for denoting consistency conditions between m...

In this paper, we exploit the theory of dense graph limits to provide a new framework to study the stability of graph partitioning methods, which we call structural consistency. Both stability under perturbation as well as asymptotic consistency (i.e., convergence with probability 1 as the sample size goes to infinity under a fixed probability model) follow from our notion of structural consist...

Finite mixtures of normal distributions are attractive in identifying the underlying group structure in the data. However, it is a challenging task to do statistical inference in normal mixture models using the method of maximum likelihood, due to the unbounded likelihood and the existence of multiple roots to the likelihood equation including a so-called spurious root. In this article we propo...

This paper provides a survey of the current state of the art in Causally-Consistent data stores. Furthermore, we present the design of Thespis, a middleware that innovatively leverages the Actor model to implement causal consistency over an industry-standard data store.

The increasing adoption of MDE (Model Driven Engineering) favored the use of large models of different types. It turns out that when the modeled system gets larger, simply computing a list of inconsistencies (as provided by existing techniques for inconsistency handling) gets less and less effective when it comes to actually fixing them. In fact, the inconsistency handling task (i.e. deciding w...

In this paper, we present constraint propagation techniques used in the OPIS scheduling system to update schedule descriptions and detect introduced inconsistencies. Our approach is summarized as follows: • A hierarchical model is used to represent resources and operations to be performed. Schedules are developed and maintained at different levels of precision which are explicitly associated wi...

1 Web Caching, Consistency, and Content Distribution 1 Arun Iyengar, Erich Nahum, Anees Shaikh, Renu Tewari IBM Research 1.

Many future computers will be shared-memory multiprocessors. These hardware systems must define for software the allowable behavior of memory. A reasonable model is sequential consistency (SC), which makes a shared memory multiprocessor behave like a multiprogrammed uniprocessor. Since SC appears to limit some of the optimizations useful for aggressive hardware implementations, researchers and ...

This paper presents a modeling approach based on deterministic and stochastic Petri nets (DSPN's) for analyzing memory consistency protocols for multiprocessors with Distributed Shared Memory (DSM). DSPN's are a numerically solvable modeling formalism with a graphical representation. The modeling approach addresses in particular the performance degradation due to the amount of message exchange,...