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A graph-based tool to embed the π-calculus into a computational DPO framework 46

A graph-based tool to embed the π-calculus into a computati...

46th International conference on current trends in theory and practice of computer science Doctoral Student Research Forum, SOFSEM-SRF 2020

作者： Andersen, Jakob L. Hellmuth, Marc Merkle, Daniel Nøjgaard, Nikolai Peressotti, Marco Department of Mathematics and Computer Science University of Southern Denmark Odense Denmark Institute of Mathematics and Computer Science University of Greifswald Germany Harvard Medical School Department of Systems Biology BostonMA United States

Graph transformation approaches have been successfully used to analyse and design chemical and biological systems. Here we build on top of a DPO framework, in which molecules are modelled as typed attributed graphs and chemical reactions are modelled as graph transformations. Edges and vertexes can be labelled with first-order terms, which can be used to encode, e.g., steric information of molecules. While targeted to chemical settings, the computational framework is intended to be very generic and applicable to the exploration of arbitrary spaces derived via iterative application of rewrite rules, such as process calculi like Milner's π-calculus. To illustrate the generality of the framework, we introduce EpiM: a tool for computing execution spaces of π-calculus processes. EpiM encodes π-calculus processes as typed attributed graphs and then exploits the existing DPO framework to compute their dynamics in the form of graphs where nodes are π-calculus processes and edges are reduction steps. EpiM takes advantage of the graph-based representation and facilities offered by the framework, like efficient isomorphism checking to prune the space without resorting to explicit structural equivalences. EpiM is available as an online Python-based tool. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Molecules

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Evolving Decision Trees for the Categorization of Software

Evolving Decision Trees for the Categorization of Software

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IEEE Annual computer Software and Applications conference Workshops (COMPSACW)

作者： Jasenko Hosic Daniel R. Tauritz Samuel A. Mulder Department of Computer Science Missouri University of Science and Technology Rolla Missouri USA Sandia National Laboratories Albuquerque New Mexico USA

current manual techniques of static reverse engineering are inefficient at providing semantic program understanding. We have developed an automated method to categorize applications in order to quickly determine pertinent characteristics. Prior work in this area has had some success, but a major strength of our approach is that it produces heuristics that can be reused for quick analysis of new data. Our method relies on a genetic programming algorithm to evolve decision trees which can be used to categorize software. the terminals, or leaf nodes, within the trees each contain values based on selected features from one of several attributes: system calls, byte n-grams, opcode n-grams, cyclomatic complexity, and bonding. the evolved decision trees are reusable and achieve average accuracies above 95% when categorizing programs based on compiler origin and versions. Developing new decision trees simply requires more labeled datasets and potentially different feature selection algorithms for other attributes, depending on the data being classified.

关键词： Decision trees Software Complexity theory Accuracy Histograms Bonding Testing

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Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning 38

Personalizing Reinforcement Learning from Human Feedback wit...

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38th conference on Neural Information Processing Systems, NeurIPS 2024

作者： Poddar, Sriyash Wan, Yanming Ivison, Hamish Gupta, Abhishek Jaques, Natasha Paul G. Allen School of Computer Science and Engineering University of Washington SeattleWA98195 United States

Reinforcement Learning from Human Feedback (RLHF) is a powerful paradigm for aligning foundation models to human values and preferences. However, current RLHF techniques cannot account for the naturally occurring differences in individual human preferences across a diverse population. When these differences arise, traditional RLHF frameworks simply average over them, leading to inaccurate rewards and poor performance for individual subgroups. To address the need for pluralistic alignment, we develop a class of multimodal RLHF methods. Our proposed techniques are based on a latent variable formulation - inferring a novel user-specific latent and learning reward models and policies conditioned on this latent without additional user-specific data. While conceptually simple, we show that in practice, this reward modeling requires careful algorithmic considerations around model architecture and reward scaling. To empirically validate our proposed technique, we first show that it can provide a way to combat underspecification in simulated control problems, inferring and optimizing user-specific reward functions. Next, we conduct experiments on pluralistic language datasets representing diverse user preferences and demonstrate improved reward function accuracy. We additionally show the benefits of this probabilistic framework in terms of measuring uncertainty, and actively learning user preferences. this work enables learning from diverse populations of users with divergent preferences, an important challenge that naturally occurs in problems from robot learning to foundation model alignment. © 2024 Neural information processing systems foundation. All rights reserved.

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Extending the theoretical Fault Localization Effectiveness Hierarchy with Empirical Results at Different Code Abstraction Levels

Extending the Theoretical Fault Localization Effectiveness H...

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IEEE Annual International computer Software and Applications conference (COMPSAC)

作者： Chung Man Tang W.K. Chan Y.T. Yu Department of Computer Science City University of Hong Kong Hong Kong City University of Hong Kong Kowloon HK

Spectrum-based fault localization techniques are semi-automated program debugging techniques that address the bottleneck of finding suspicious program locations for diagnosis. they assess the fault suspiciousness of individual program locations based on the code coverage data achieved by executing the program under debugging over a test suite. A program location can be viewed at different abstraction levels, such as a statement in the source code or an instruction compiled from the source code. In general, a program location at one code abstraction level can be transformed into zero to more program locations at another abstraction level. Although programmers usually debug at the source code level, the code is actually executed at a lower level. It is unclear whether the same techniques applied at different code abstraction levels may achieve consistent results. In this paper, we study a suite of spectrum-based fault localization techniques at both the source and instruction code levels in the context of an existing theoretical hierarchy to assess whether their effectiveness is consistent across the two levels. Our study extends the theoretical hierarchy with empirically validated relationships across two code abstraction levels toward an integration of the theory and practice of fault localization.

关键词： Erbium Context Debugging Measurement Aggregates Instruments computers

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6543 LNCS卷 V-VI页

作者： Černá, Ivana Gyimothy, Tibor Hromkovč, Juraj Jeffery, Keith Královič, Rastislav Vukolic, Marko Wolf, Stefan

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A Ihara-Bass Formula for Non-Boolean Matrices and Strong Refutations of Random CSPs 23

A Ihara-Bass Formula for Non-Boolean Matrices and Strong Ref...

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38th Computational Complexity conference, CCC 2023

作者： D'Orsi, Tommaso Trevisan, Luca Department of Computer Science ETH Zürich Switzerland Department of Computing Sciences Bocconi University Milano Italy

ISBN: (纸本)9783959772822

We define a novel notion of "non-backtracking" matrix associated to any symmetric matrix, and we prove a "Ihara-Bass" type formula for it. We use this theory to prove new results on polynomial-time strong refutations of random constraint satisfaction problems with k variables per constraints (k-CSPs). For a random k-CSP instance constructed out of a constraint that is satisfied by a p fraction of assignments, if the instance contains n variables and nk/2/є2 constraints, we can efficiently compute a certificate that the optimum satisfies at most a p + Ok(є) fraction of constraints. Previously, this was known for even k, but for odd k one needed nk/2(log n)O(1)/є2 random constraints to achieve the same conclusion. Although the improvement is only polylogarithmic, it overcomes a significant barrier to these types of results. Strong refutation results based on current approaches construct a certificate that a certain matrix associated to the k-CSP instance is quasirandom. Such certificate can come from a Feige-Ofek type argument, from an application of Grothendieck's inequality, or from a spectral bound obtained with a trace argument. the first two approaches require a union bound that cannot work when the number of constraints is o(n⌈k/2⌉) and the third one cannot work when the number of constraints is o(nk/2√log n). We further apply our techniques to obtain a new PTAS finding assignments for k-CSP instances with nk/2/є2 constraints in the semi-random settings where the constraints are random, but the sign patterns are adversarial. © Tommaso d'Orsi and Luca Trevisan;licensed under Creative Commons License CC-BY 4.0.

关键词： Matrix algebra

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Liver segmentation using location and intensity probabilistic atlases

Liver segmentation using location and intensity probabilisti...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Negar Farzaneh Shadrokh Samavi S.M. Reza Soroushmehr Hirenkumar Patel Samuel Habbo-Gavin David Paul Fessell Kevin R. Ward Kayvan Najarian Michigan Center for Integrative Research in Critical Care University of Michigan Ann Arbor MI USA Department of Emergency Medicine University of Michigan Ann Arbor MI USA Department of Computer Science University of Michigan Ann Arbor MI USA University of Michigan Medical School Ann Arbor MI USA

In a variety of injuries and illnesses, internal organs in the abdominal and pelvic regions, in particular liver, may be compromised. In the current practice, CT scans of liver are visually inspected to investigate the integrity of the organ. However, the size and complexity of the CT images limits the reliability of visual inspection to accurately assess the health of liver. computer-aided image analysis can create fast and quantitative assessment of liver from the CT, in particular in the environments where access to skilled radiologists may be limited. In this paper we propose a hierarchical method based on probabilistic models of position and intensity of voxels for automated segmentation of liver that achieves the Dice similarity coefficient of higher than 89%.

关键词： Liver Computed tomography Image segmentation Bones Probabilistic logic Estimation Injuries

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Data management challenges for GRID computing 1

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29th conference on current trends in theory and practice of Informatics, SOFSEM 2002

作者： Jeffery, Keith G. Rutherford Appleton Laboratory United Kingdom

ISBN: (数字)9783540361374

ISBN: (纸本)354000145X

During 1999 the UK Office of science and Technology wished to find a paradigm for future scientific R&D IT support. the author was asked to produce a paper and did so, proposing a 3-layer GRIDs architecture. At about the same time, Ian Foster and Carl Kesselman published 'the GRID' - commonly known as the 'GRID Bible' which proposed a network of linked supercomputer centres. the 3-layer architecture proposed in UK has at the base the computation/ data layer which corresponds with that of Foster & Kesselman but extends it to include detectors and instruments such as those on particle physics accelerators or on satellites. the middle information layer provides to the end-user (or other IT systems) a homogeneous view over heterogeneous data, including analytical (statistical) software and modelling and simulation facilities. the highest, knowledge, layer stores 'commonly accepted justified belief' i. e. scientific papers including hypotheses created by people -with hyperlinks to information and software systems used to allow replication of the experiments - and the results of data mining which is essentially automated hypothesis creation. the knowledge is also used in intelligent detectors in the lowest layer to improve the relevance of collected data, and in query/answer assist software in the middle information layer. An architectural implementation based on metadata, intelligent agents and brokers (i. e. services) was proposed. Within UK the e-science R&D programme since April 2001 has implemented the Foster & Kesselman software. the limitations are now known to be as predicted in 1999 and a further R&D programme aimed less at metacomputing and more at e-business, e-information and e-learning is proposed. Meantime, the Global Grid Forum has proposed (late 2001) an Open Grid Services Architecture, based on W3C Web Services, so finally realising the convergence implicit in the 3-layer GRIDs model. © Springer-Verlag Berlin Heidelberg 2002.

关键词： e-science

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2009年 5404 LNCS卷 v-vi页

作者： Nielsen, Mogens Kučera, Antonín Miltersen, Peter Bro Palamidessi, Catuscia Tůma, Petr University of Aarhus Aarhus Graduate School of Science Ny Munkegade Bldg 1521-110 DK-8000 Aarhus C Denmark Masaryk University Department of Informatics Botanická 68a 60200 Brno Czech Republic University of Aarhus Department of Computer Science IT-parken Aabogade 34 DK-8200 Aarhus N Denmark Frank Valencia Ecole Polytechnique Rue de Saclay 91128 Palaiseau Cedex France Charles University Departmetn of Mathematics and Physics Malostranské náměstí 25 118 00 Prague 1 Malá Strana Czech Republic

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Improving clinical models based on knowledge extracted from current datasets: A new approach

Improving clinical models based on knowledge extracted from ...

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Annual International conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： D. Mendes S. Paredes T. Rocha P. Carvalho J. Henriques J. Morais CISUC University of Coimbra Computer Science and Systems Engineering Department Polytechnic Institute of Coimbra (IPC/ISEC) Investigators of the National Registry on Acute Coronary Syndromes Portuguese Society of Cardiology

ISBN: (纸本)9781457702198

the Cardiovascular Diseases (CVD) are the leading cause of death in the world, being prevention recognized to be a key intervention able to contradict this reality. In this context, although there are several models and scores currently used in clinical practice to assess the risk of a new cardiovascular event, they present some limitations. the goal of this paper is to improve the CVD risk prediction taking into account the current models as well as information extracted from real and recent datasets. this approach is based on a decision tree scheme in order to assure the clinical interpretability of the model. An innovative optimization strategy is developed in order to adjust the decision tree thresholds (rule structure is fixed) based on recent clinical datasets. A real dataset collected in the ambit of the National Registry on Acute Coronary Syndromes, Portuguese Society of Cardiology is applied to validate this work. In order to assess the performance of the new approach, the metrics sensitivity, specificity and accuracy are used. this new approach achieves sensitivity, a specificity and an accuracy values of, 80.52%, 74.19% and 77.27% respectively, which represents an improvement of about 26% in relation to the accuracy of the original score.

关键词： Optimization Genetic algorithms Decision trees Cardiology Modeling Sociology Statistics

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