The paper presents a non-monotonic inference relation on a language containing a conditional that satisfies the Ramsey Test. The logic is a weakening of classical logic and preserves many of the ‘paradoxes of implication’ associated with the material implication. It is argued, however, that once one makes the proper distinction between supposing that something is the case and accepting that it ...

Keywords-Fuzzy reasoning, Fuzzy system, Variable weighted synthesis inference method, CRI method, Fuzzy control. 1. I N T R O D U C T I O N It is well known that fuzzy inference is a theoretical foundation of fuzzy control systems and fuzzy expert systems. At present, general fuzzy inference methods include the CRI (compositional rules of inference) method, (+,-)-centroid method, simple inferen...

In the logical view on IR systems, retrieval is interpreted as implication [Rijsbergen 86]: Let d denote a document (represented as logical formula) and q a query, then retrieval deals with the task of finding those documents which imply the query, i.e. for which the formula d → q is true. Due to the intrinsic uncertainty and vagueness of IR, we have to switch to uncertain inference. Using a pr...

Bayesian nonparametric inferential procedures based on Markov chain Monte Carlo marginal methods typically yield point estimates in the form of posterior expectations. Though very useful and easy to implement in a variety of statistical problems, these methods may suffer from some limitations if used to estimate non-linear functionals of the posterior distribution. The main goal is to develop a...

In spectrometer measurement, it is very important to accurately calibrate the wavelength of all target characteristic spectra. Although calibration methods have long been investigated, no techniques designed for scanning, double-layer, secondary diffraction, linear-array CCD spectrometer, best our knowledge. Based on grating diffraction equation and experimental results, a mathematical model wa...

We study the implication problem for the combined class of functional and full hierarchical dependencies in the presence of SQL’s NOT NULL constraints. Two different notions of implication are addressed: one where a dependency is implied by the given set of dependencies plus the underlying schema, and one where a dependency is implied by the given set of dependencies alone. We establish axiomat...

Dynamic topic models (DTMs) are very effective in discovering topics and capturing their evolution trends in time series data. To do posterior inference of DTMs, existing methods are all batch algorithms that scan the full dataset before each update of the model and make inexact variational approximations with mean-field assumptions. Due to a lack of a more scalable inference algorithm, despite...

In regular inference, a regular language is inferred from answers to a finite set of membership queries, each of which asks whether the language contains a certain word. One of the most well-known regular inference algorithms is the L∗ algorithm due to Dana Angluin. However, there are almost no extensions of these algorithms to the setting of timed systems. We extend Angluin’s algorithm for on-...

Consensus Monte Carlo is an algorithm for conducting Monte Carlo based Bayesian inference on large data sets distributed across many worker machines in a data center. The algorithm operates by running a separate Monte Carlo algorithm on each worker machine, which only sees a portion of the full data set. The worker-level posterior samples are then combined to form a Monte Carlo approximation to...