作者：
Cussens, JamesUniv York
Dept Comp Sci York YO10 5GE N Yorkshire England Univ York
York Ctr Complex Syst Anal York YO10 5GE N Yorkshire England
This paper presents a method for approximating posterior distributions over the parameters of a given PRISM program. A sequential approach is taken where the distribution is updated one datapoint at a time. This makes...
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This paper presents a method for approximating posterior distributions over the parameters of a given PRISM program. A sequential approach is taken where the distribution is updated one datapoint at a time. This makes it applicable to online learning situations where data arrives over time. The method is applicable whenever the prior is a mixture of products of Dirichlet distributions. In this case the true posterior will be a mixture of very many such products. An approximation is effected by merging products of Dirichlet distributions. An analysis of the quality of the approximation is presented. Due to the heavy computational burden of this approach, the method has been implemented in the Mercury logicprogramming language. Initial results using a hidden Markov model and a probabilistic graph are presented.
ProbLog is a probabilistic extension of Prolog. Given the complexity of exact inference under ProbLog's semantics, in many applications in machine learning approximate inference is necessary. Current approximate i...
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ProbLog is a probabilistic extension of Prolog. Given the complexity of exact inference under ProbLog's semantics, in many applications in machine learning approximate inference is necessary. Current approximate inference algorithms for ProbLog however require either dealing with large numbers of proofs or do not guarantee a low approximation error. In this paper we introduce a new approximate inference algorithm which addresses these shortcomings. Given a user-specified parameter k, this algorithm approximates the success probability of a query based on at most k proofs and ensures that the calculated probability p is (1-1/e)p (au)a parts per thousand currency signpa parts per thousand currency signp (au), where p (au) is the highest probability that can be calculated based on any set of k proofs. Furthermore a useful feature of the set of calculated proofs is that it is diverse. Our experiments show the utility of the proposed algorithm.
Road curb detection and tracking is essential for the autonomous driving of intelligent vehicles on highways and urban roads. In this paper, we present a fast and robust road curb detection algorithm using 3D lidar da...
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ISBN:
(纸本)9781467327435;9781467327428
Road curb detection and tracking is essential for the autonomous driving of intelligent vehicles on highways and urban roads. In this paper, we present a fast and robust road curb detection algorithm using 3D lidar data and Integral Laser Points (ILP) features. Range and intensity data of the 3D lidar is decomposed into elevation data and data projected on the ground plane. First, left and right road curbs are detected for each scan line using the ground projected range and intensity data and line segment features. Then, curb points of each scan line are determined using elevation data. The ILP features are proposed to speed up the both detection procedures. Finally, parabola model and RANSAC algorithm is used to fit the left and right curb points and generate vehicle controlling parameters. The proposed method and feature provide fast and reliable road curb detection speed and performance. Experiments show good results on various highways and urban roads under different situations.
Single-ISA heterogeneous multi-core processors are typically composed of small (e. g., in-order) power-efficient cores and big (e. g., out-of-order) high-performance cores. The effectiveness of heterogeneous multi-cor...
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ISBN:
(纸本)9781467304764
Single-ISA heterogeneous multi-core processors are typically composed of small (e. g., in-order) power-efficient cores and big (e. g., out-of-order) high-performance cores. The effectiveness of heterogeneous multi-cores depends on how well a scheduler can map workloads onto the most appropriate core type. In general, small cores can achieve good performance if the workload inherently has high levels of ILP. On the other hand, big cores provide good performance if the workload exhibits high levels of MLP or requires the ILP to be extracted dynamically. This paper proposes Performance Impact Estimation (PIE) as a mechanism to predict which workload-to-core mapping is likely to provide the best performance. PIE collects CPI stack, MLP and ILP profile information, and estimates performance if the workload were to run on a different core type. Dynamic PIE adjusts the scheduling at run-time and thereby exploits fine-grained time-varying execution behavior. We show that PIE requires limited hardware support and can improve system performance by an average of 5.5% over recent state-of-the-art scheduling proposals and by 8.7% over a sampling-based scheduling policy.
Introducing fuzzy predicates in inductive logic programming may serve two different purposes: allowing for more adaptability when learning classical rules or getting more expressivity by learning fuzzy rules. This lat...
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Introducing fuzzy predicates in inductive logic programming may serve two different purposes: allowing for more adaptability when learning classical rules or getting more expressivity by learning fuzzy rules. This latter concern is the topic of this paper. Indeed, introducing fuzzy predicates in the antecedent and in the consequent of rules may convey different non-classical meanings. The paper focuses on the learning of gradual and certainty rules, which have an increased expressive power and have no simple crisp counterpart. The benefit and the application domain of each kind of rules are discussed. Appropriate confidence degrees for each type of rules are introduced. These confidence degrees play a major role in the adaptation of the classical FOIL inductive logic programming algorithm to the induction of fuzzy rules for guiding the learning process. The method is illustrated on a benchmark example and a case-study database.
Model transformation by example [18] is a novel approach in model-driven software engineering to derive model transformation rules from an initial prototypical set of interrelated source and target models, which descr...
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ISBN:
(纸本)9781595934802
Model transformation by example [18] is a novel approach in model-driven software engineering to derive model transformation rules from an initial prototypical set of interrelated source and target models, which describe critical cases of the model transformation problem in a purely declarative way. In the current paper, we automate this approach using inductive logic programming [14] which aims at the inductive construction of first-order clausal theories from examples and background knowledge.
Effectiveness and efficiency are two most important properties of ILP approaches. For both top-down and bottom-up search-based approaches, greater efficiency is usually gained at the expense of effectiveness. In this ...
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ISBN:
(纸本)9783540696087
Effectiveness and efficiency are two most important properties of ILP approaches. For both top-down and bottom-up search-based approaches, greater efficiency is usually gained at the expense of effectiveness. In this paper, we propose a bottom-up approach, called ILP by instance patterns, for the problem of concept learning in ILP. This approach is based on the observation that each example has its own pieces of description in the background knowledge, and the example together with these descriptions constitute a instance of the concept subject to learn. Our approach first captures the instance structures by patterns, then constructs the final theory purely from the patterns. On the effectiveness aspect, this approach does not assume determinacy of the learned concept. On the efficiency aspect, this approach is more efficient than existing ones due to its constructive nature, the fact that after the patterns are obtained, both the background and examples are not needed anymore, and the fact that it does not perform coverage test and needs no theorem prover.
Background: We present the BioNLP 2011 Shared Task Bacteria Track, the first Information Extraction challenge entirely dedicated to bacteria. It includes three tasks that cover different levels of biological knowledge...
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Background: We present the BioNLP 2011 Shared Task Bacteria Track, the first Information Extraction challenge entirely dedicated to bacteria. It includes three tasks that cover different levels of biological knowledge. The Bacteria Gene Renaming supporting task is aimed at extracting gene renaming and gene name synonymy in PubMed abstracts. The Bacteria Gene Interaction is a gene/protein interaction extraction task from individual sentences. The interactions have been categorized into ten different sub-types, thus giving a detailed account of genetic regulations at the molecular level. Finally, the Bacteria Biotopes task focuses on the localization and environment of bacteria mentioned in textbook articles. We describe the process of creation for the three corpora, including document acquisition and manual annotation, as well as the metrics used to evaluate the participants' submissions. Results: Three teams submitted to the Bacteria Gene Renaming task;the best team achieved an F-score of 87%. For the Bacteria Gene Interaction task, the only participant's score had reached a global F-score of 77%, although the system efficiency varies significantly from one sub-type to another. Three teams submitted to the Bacteria Biotopes task with very different approaches;the best team achieved an F-score of 45%. However, the detailed study of the participating systems efficiency reveals the strengths and weaknesses of each participating system. Conclusions: The three tasks of the Bacteria Track offer participants a chance to address a wide range of issues in Information Extraction, including entity recognition, semantic typing and coreference resolution. We found commond trends in the most efficient systems: the systematic use of syntactic dependencies and machine learning. Nevertheless, the originality of the Bacteria Biotopes task encouraged the use of interesting novel methods and techniques, such as term compositionality, scopes wider than the sentence.
We present a novel technique for jointly predicting semantic arguments for lexical predicates. The task is to find the best matching between semantic roles and sentential spans, subject to structural constraints that ...
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ISBN:
(纸本)9781622765027
We present a novel technique for jointly predicting semantic arguments for lexical predicates. The task is to find the best matching between semantic roles and sentential spans, subject to structural constraints that come from expert linguistic knowledge (e.g., in the FrameNet lexicon). We formulate this task as an integer linear program (ILP); instead of using an off-the-shelf tool to solve the ILP, we employ a dual decomposition algorithm, which we adapt for exact decoding via a branch-and-bound technique. Compared to a baseline that makes local predictions, we achieve better argument identification scores and avoid all structural violations. Runtime is nine times faster than a proprietary ILP solver.
Despite the increasing popularity of Free-Space Optics (FSO) in wireless mesh networks, reliability is still a major concern. Due to the strong dependence of FSO link availability on weather conditions (e.g., fog, clo...
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ISBN:
(纸本)9781467309202
Despite the increasing popularity of Free-Space Optics (FSO) in wireless mesh networks, reliability is still a major concern. Due to the strong dependence of FSO link availability on weather conditions (e.g., fog, cloud, air turbulence) using KF links is inevitable, both for backup and signaling. In addition, reconfiguration of FSO transceivers could preserve network reliability when several connections suffer outages. In this paper, we find the optimal reconfiguration of transceivers and rerouting of traffic flows using an integer-linear program (ILP). The link availability prediction is used as an input and the overall throughput of the network is maximized while guaranteeing fairness to all traffic demands. To avoid the complexity of the ILP, an efficient probabilistic heuristic that computes a set of schedules for dynamic reconfiguration of FSO transceivers is proposed. We show that this heuristic achieves a high fraction of the optimal throughput, as verified by extensive simulations.
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