The Levo high ILP microarchitecture is described and evaluated. Levo employs instruction time-tags and active stations to ensure correct operation in a rampantly speculative and out-oforder resource flow execution model. The Tomasulo-algorithm-like broadcast buses are segmented; their lengths are constant, that is, do not increase with machine size. This helps to make Levo scalable. Known High-...

We apply Inductive Logic Programming (ILP) for inducing trading rules formed out of combinations of technical indicators from historical market data. To do this, we first identify ideal trading opportunities in the historical data, and then feed these as examples to an ILP learner, which will try to induce a description of them in terms of a given set of indicators. The main contributions of th...

ILP has been successfully applied to a variety of tasks. Nevertheless, ILP systems have huge time and storage requirements, owing to a large search space of possible clauses. Therefore, clever search strategies are needed. One promising family of search strategies is that of stochastic local search methods. These methods have been successfully applied to propositional tasks, such as satisfiabil...

Inductive Logic Programming has been very successful in application to multirelational predictive tasks. Sophisticated predictive ILP systems, such as Progol and foil, can achieve high predictive accuracy, while the learning results remain understandable. Although boosting [1] is an established method to promote predictive accuracy of weak algorithms, there have been relatively few efforts to a...

Inductive Logic Programming (ILP) deals with the problem of finding a hypothesis covering positive examples and excluding negative examples, where both hypotheses and examples are expressed in first-order logic. In this paper we employ constraint satisfaction techniques to model and solve a problem known as template ILP consistency, which assumes that the structure of a hypothesis is known and ...

Integer Linear Programming (ILP) has a broad range of applications in various areas artificial intelligence. Yet spite recent advances, we still lack thorough understanding which structural restrictions make ILP tractable. Here study instances consisting small number “global” variables and/or constraints such that the remaining part instance consists and otherwise independent components; this i...

Building reconstruction and building model generation nowadays receives more and more attention. In this context models such as formal grammars play a major role in 3D geometric modelling. Up to now, models have been designed manually by experts such as architects. Hence, this paper describes an Inductive Logic Programming (ILP) based approach for learning semantic models and grammar rules of b...

The use of Inductive Logic Programming (ILP) for the construction of a user model allows possibilities such as the use of intensional background knowledge and the ability to present a set of comprehensible rules to the user. A few simple concepts have previously been modelled using standard ILP methods but a concept of the complexity attempted within this dissertation brings problems which have...

The intention of this study was to estimate the pharmacological advantage of a clinically applicable method of isolated liver perfusion (ILP) over hepatic artery infusion (HAI) administering various doses of 5-fluorouracil (FUra). FUra concentrations were measured using high-performance liquid chromatography in liver tissue (pigs and rats), hepatic tumor tissue (rats), and in the systemic circu...

Service requests of intra-datacenter networks (intraDCNs) are different from traffic demands of traditional transport networks in the following features: 1) The latter is typically generated between dedicated node pairs that only require sufficient transmission bandwidth, i.e., frequency spectrum. IntraDCN service requests, in contrast, require IT resources, such as computational, memory and st...