ppxscal/embedding_network huggingface dataset:
Epistemology probabilized
Authors: Richard Jeffrey
Venue: Technologies for constructing intelligent systems: tools (2002)

Here is a framework for judgment in terms of a continuum of "subjective" probabilities, a framework in which probabilistic judgments need not stand on a foundation of certainties. In place of propositional data bases, this radical probabilism ("probabilities all the way down to the roots") envisages full or partial probability assignments to probability spaces, together with protocols for revising those assignments and their interconnections in the light of fresh empirical or logico-mathematical input. This input need not be of the limiting 0-or-1 sort. Updating by ordinary conditioning is generalized (sec. 2.2) to probability kinematics, where an observation on a random variable X need not single out one value, but may prompt a new probability distribution Q over all values of X.The effect of an observation itself, apart from the influence of prior probabilities (sec. 3), is given by the ("Bayes') factors new odds/old odds by which the observer's odds between hypotheses are updated. We are not generally interested in adopting an observer's new odds as our own, for those are influenced by the observer's old odds, not ours. It is rather the observer's Bayes's factors that we need in order to use that observation in our own judgments. An account of collaborative updating is presented in these terms.Jon Dorling's bayesian solution of the Duhem-Quine "holism" problem is sketched in sec. 4.We finish with a brief look at the historical setting of radical probabilism (sec. 5), and an indication of how "real" probabilities can be accomodated in subjectivistic terms (sec. 6).
Towards context sensitive information inference
Authors: D. Song, P. D. Bruza
Venue: Journal of the American Society for Information Science and Technology (2003)

Humans can make hasty, but generally robust judgements about what a text fragment is, or is not, about. Such judgements are termed information inference. This article furnishes an account of information inference from a psychologistic stance. By drawing on theories from nonclassical logic and applied cognition, an information inference mechanism is proposed that makes inferences via computations of information flow through an approximation of a conceptual space. Within a conceptual space information is represented geometrically. In this article, geometric representations of words are realized as vectors in a high dimensional semantic space, which is automatically constructed from a text corpus. Two approaches were presented for priming vector representations according to context. The first approach uses a concept combination heuristic to adjust the vector representation of a concept in the light of the representation of another concept. The second approach computes a prototypical concept on the basis of exemplar trace texts and moves it in the dimensional space according to the context. Information inference is evaluated by measuring the effectiveness of query models derived by information flow computations. Results show that information flow contributes significantly to query model effectiveness, particularly with respect to precision. Moreover, retrieval effectiveness compares favorably with two probabilistic query models, and another based on semantic association. More generally, this article can be seen as a contribution towards realizing operational systems that mimic text-based human reasoning.
Development of NPACI Grid Application Portals and Portal Web Services
Authors: M. Thomas, J. Boisseau, M. Dahan, C. Mills, S. Mock, K. Mueller
Venue: Cluster Computing (2003)

Grid portals and services are emerging as convenient mechanisms for providing the scientific community with familiar and simplified interfaces to the Grid. Our experiences in implementing computational grid portals, and the services needed to support them, has led to the creation of GridPort: a unique, integrated, layered software system for building portals and hosting portal services that access Grid services. The usefulness of this system has been successfully demonstrated with the implementation of several application portals. This system has several unique features: the software is portable and runs on most webservers; written in Perl/CGI, it is easy to support and modify; a single API provides access to a host of Grid services; it is flexible and adaptable; it supports single login between multiple portals; and portals built with it may run across multiple sites and organizations. In this paper we summarize our experiences in building this system, including philosophy and design choices and we describe the software we are building that support portal development, portal services. Finally, we discuss our experiences in developing the GridPort Client Toolkit in support of remote Web client portals and Grid Web services.
Submodular Returns and Greedy Heuristics for Queueing Scheduling Problems
Authors: R. Garbe, K. D. Glazebrook
Venue: Operations Research (1998)

We consider a range of controlled stochastic systems satisfying conservation laws together with a reducibility property that says that appropriate laws continue to hold when access to the system is restricted to a subset of all possible demand (job, customer) types. We show that for linear objectives, the optimum system-wide performance is a nondecreasing submodular (or supermodular) function of the subset chosen and that these properties are inherited from the geometry of the performance space concerned. These results are of considerable interest in their own right, but they also motivate the use of greedy heuristics for the solution of a range of job selection and scheduling problems which have hitherto seemed intractable. Computational experience suggests that such heuristics perform very well.
Holmes: a prototype for the targeted search of information about hi-tech companies
Authors: Nicola Capuano, Matteo Gaeta, Fabio Gasparetti, Alessandro Micarelli
Venue: Second international workshop on Intelligent systems design and application (2002)

A system prototype for intelligent agents is presented. The system, called Holmes, is specialized in adaptive information filtering and searching of interesting information on the Web. It allows for the execution of searches by exploiting both indications provided by traditional search engines and autonomous exploration. In both cases, we use the model of the user, in the first case to make the proposed results more significant by modifying the proposed order, and in the second one to guide the exploration.
Asymptotic Mean and Variance of Electric Power Generation System Production Costs Via Recursive Computation of the Fundamental Matrix of a Markov Chain
Authors: Fen-Ru Shih, Mainak Mazumdar, Jeremy A. Bloom
Venue: Operations Research (1999)

The cost of producing electricity during a given time interval is a random variable that depends both on the availability of the generating units during the study horizon and on the magnitude of the load. Based upon a Markov model, we present a recursive scheme for estimating the asymptotic mean and variance of the production cost. These computations are difficult because the state space for a typical power generation system is very large and because the asymptotic variance depends upon the fundamental matrix. Its computation requires the inversion of a matrix whose dimension depends on the size of the state space. The recursion relations given here preclude the need for such matrix inversion and provide approximate estimates that compare very favorably with a realistic Monte Carlo simulation.
A note on the energy norm for a singularly perturbed model problem
Authors: Gerd Kunert
Venue: Computing (2002)

This paper considers a singularly perturbed reaction diffusion problem. It is investigated whether adaptive approaches are successful to design robust solution procedures. A key ingredient is the a posteriori error estimator. Since robust and mathematically analysed error estimation is possible in the energy norm, the focus is on this choice of norm and its implications. The numerical performance for several model problems confirms that the proposed adaptive algorithm (in conjunction with an energy norm error estimator) produces optimal results. Hence the energy norm is suitable for the purpose considered here. The investigations also provide valuable justification for forthcoming research.
Concepts, Technical Issues, and Uses of the Russell-Yasuda Kasai Financial Planning Model
Authors: David R. Carino, David H. Myers, William T. Ziemba
Venue: Operations Research (1998)

This paper discusses technical aspects of the Russell-Yasuda Kasai financial planning model. These include the models for the discrete distribution scenario generation processes for the uncertain parameters of the model, the mathematical approach used to develop the infinite-horizon end-effects part of the model, a comparison of algorithms used in the model's solution, and a comparison of the multistage stochastic linear programming model with the previous technology, static mean-variance analysis. Experience and benefits of the model in Yasuda-Kasai's financial planning process is also discussed.
Matrix Decomposition Algorithms for Modified Spline Collocation for Helmholtz Problems
Authors: Bernard Bialecki, Graeme Fairweather, Andreas Karageorghis
Venue: SIAM Journal on Scientific Computing (2002)

We consider the solution of various boundary value problems for the Helmholtz equation in the unit square using a nodal cubic spline collocation method and modifications of it which produce optimal (fourth-) order approximations. For the solution of the collocation equations, we formulate matrix decomposition algorithms, fast direct methods which employ fast Fourier transforms and require O(N2 log N) operations on an N &times; N uniform partition of the unit square. A computational study confirms the published analysis for the Dirichlet problem and indicates that similar results hold for Neumann, mixed, and periodic boundary conditions. The numerical results also exhibit superconvergence phenomena not reported in earlier studies.
Learning from examples with unspecified attribute values
Authors: Sally A. Goldman, Stephen S. Kwek, Stephen D. Scott
Venue: Information and Computation (2003)

A challenging problem within machine learning is how to make good inferences from data sets in which pieces of information are missing. While it is valuable to have algorithms that perform well for specific domains, to gain a fundamental understanding of the problem, one needs a "theory" about how to learn with incomplete data. The important contribution of such a theory is not so much the specific algorithmic results, but rather that it provides good ways of thinking about the problem formally. In this paper we introduce the unspecified attribute value (UAV) learning model as a first step towards a theoretical framework for studying the problem of learning from incomplete data in the exact learning framework.In the UAV learning model, an example x is classified positive (resp., negative) if all possible assignments for the unspecified attributes result in a positive (resp., negative) classification. Otherwise the classification given to x is "?"(for unknown). Given an example x in which some attributes are unspecified, the oracle UAV-MQ responds with the classification of x. Given a hypothesis h, the oracle UAV-EQ returns an example x (that could have unspecified attributes) for which h(x) is incorrect.We show that any class of functions learnable in Angluin's exact model using the MQ and EQ oracles is also learnable in the UAV model using the MQ and UAV-EQ oracles as long as the counterexamples provided by the UAV-EQ oracle have a logarithmic number of unspecified attributes. We also show that any class learnable in the exact model using the MQ and EQ oracles is also learnable in the UAV model using the UAV-MQ and UAV-EQ oracles as well as an oracle to evaluate a given boolean formula on an example with unspecified attributes. (For some hypothesis classes such as decision trees and unate formulas the evaluation can be done in polynomial time without an oracle.) We also study the learnability of a universal class of decision trees under the UAV model and of DNF formulas under a representation-dependent variation of the UAV model.
Scalable robust covariance and correlation estimates for data mining
Authors: Fatemah A. Alqallaf, Kjell P. Konis, R. Douglas Martin, Ruben H. Zamar
Venue: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining (2002)

Covariance and correlation estimates have important applications in data mining. In the presence of outliers, classical estimates of covariance and correlation matrices are not reliable. A small fraction of outliers, in some cases even a single outlier, can distort the classical covariance and correlation estimates making them virtually useless. That is, correlations for the vast majority of the data can be very erroneously reported; principal components transformations can be misleading; and multidimensional outlier detection via Mahalanobis distances can fail to detect outliers. There is plenty of statistical literature on robust covariance and correlation matrix estimates with an emphasis on affine-equivariant estimators that possess high breakdown points and small worst case biases. All such estimators have unacceptable exponential complexity in the number of variables and quadratic complexity in the number of observations. In this paper we focus on several variants of robust covariance and correlation matrix estimates with quadratic complexity in the number of variables and linear complexity in the number of observations. These estimators are based on several forms of pairwise robust covariance and correlation estimates. The estimators studied include two fast estimators based on coordinate-wise robust transformations embedded in an overall procedure recently proposed by [14]. We show that the estimators have attractive robustness properties, and give an example that uses one of the estimators in the new Insightful Miner data mining product.
Short-Term Generation Asset Valuation: A Real Options Approach
Authors: Chung-Li Tseng, Graydon Barz
Venue: Operations Research (2002)

This paper discusses using real options to value power plants with unit commitment constraints over a short-term period. We formulate the problem as a multistage stochastic problem and propose a solution procedure that integrates forward-moving Monte Carlo simulation with backward-moving dynamic programming. We assume that the power plant operator maximizes expected profit by deciding in each hour whether or not to run the unit, that a certain lead time for commitment and decommitment decisions is necessary to start up and shut down a unit, and that these commitment decisions, once made, are subject to physical constraints such as minimum uptime and downtime. We also account for the costs associated with starting up and shutting down a unit. Last, we assume that there are hourly markets for both electricity and the fuel used by the generator and that their prices follow Ito processes. Using numerical simulation, we show that failure to consider physical constraints may significantly overvalue a power plant.
Factors affecting the adoption and diffusion of XML and web services standards for E-business systems
Authors: Minder Chen
Venue: International Journal of Human-Computer Studies (2003)

Integration is a very important issue in e-business systems integration. There are three basic mechanisms to integrate diverse applications: data interchange, application program interfaces (API), and shared repositories. Standards and standardization efforts play important roles in all three areas. XML is a standard for defining data interchange standards. Web services are a set of standards for calling remote procedures over the Internet. UDDI and other e-business registries are examples of shared repositories. This paper discusses the XML and Web Services (including UDDI) standard-related technologies in the context of e-business systems. A technology adoption life cycle model is adapted to analyse various stages of standards adoption. Organizations that tend to adopt e-business standards in each stage are identified. Based on our study of e-business standards and research of relevant literatures, several factors that affect the adoption decision of e-business standards are identified. The implications of these factors are discussed. Two case studies of the implementation of e-business standards are presented. Further studies of how standards may affect the success of e-business strategies and how companies should evaluate and implement e-business standards are proposed.
Introduction
Authors: Aviel D. Rubin
Venue: Communications of the ACM (2003)

In the time span of just a few years, wireless local area networking went from being a novelty to revolutionizing the way many organizations connect their computers. Visit any major department store, hospital, or office building, and you will encounter 802.11 cards in all of the PCs and access points hanging from the ceiling. The speed with which wireless networking has caught on is not surprising, as 802.11b offers up to 11Mbps of bandwidth, and a range of several hundred feet. Newer standards, such as 802.11g, promise five times the speed. Multiple wireless access points can be easily installed on the same network to increase the coverage area, so that an entire building can be easily connected. Conversely, wiring buildings with Ethernet is expensive and limits the locations from which networked computers can be used.
Efficient selection of feature sets possessing high coefficients of determination based on incremental determinations
Authors: Ronaldo F. Hashimoto, Edward R. Dougherty, Marcel Brun, Zheng-Zheng Zhou, Michael L. Bittner, Jeffrey M. Trent
Venue: Signal Processing (2003)

Feature selection is problematic when the number of potential features is very large. Absent distribution knowledge, to select a best feature set of a certain size requires that all feature sets of that size be examined. This paper considers the question in the context of variable selection for prediction based on the coefficient of determination (CoD). The CoD varies between 0 and 1, and measures the degree to which prediction is improved by using the features relative to prediction in the absence of the features. It examines the following heuristic: if we wish to find feature sets of size m with CoD exceeding δ, what is the effect of only considering a feature set if it contains a subset with CoD exceeding λ < δ? This means that if the subsets do not possess sufficiently high CoD, then it is assumed that the feature set itself cannot possess the required CoD. As it stands, the heuristic cannot be applied since one would have to know the CoDs beforehand. It is meaningfully posed by assuming a prior distribution on the CoDs. Then one can pose the question in a Bayesian framework by considering the probability P(θ > δ | max{θ1,θ2,...,θv} < λ), where θ is the CoD of the feature set and θ1,θ2,...,θv are the CoDs of the subsets. Such probabilities allow a rigorous analysis of the following decision procedure: the feature set is examined if max{θ1,θ2,...,θv} ≥ λ. Computational saving increases as λ increases, but the probability of missing desirable feature sets increases as the increment δ - λ decreases; conversely, computational saving goes down as λ decreases, but the probability of missing desirable feature sets decreases as δ - λ increases. The paper considers various loss measures pertaining to omitting feature sets based on the criteria. After specializing the matter to binary features, it considers a simulation model, and then applies the theory in the context of microarray-based genomic CoD analysis. It also provides optimal computational algorithms.
A New Analytic Framework for Dynamic Mobility Management of PCS Networks
Authors: Chien-Hsing Wu, Huang-Pao Lin, Leu-Shing Lan
Venue: IEEE Transactions on Mobile Computing (2002)

This paper presents a new analytic framework for dynamic location management of PCS networks. Based on the theory of hexagonal cellular patterns, a novel two-dimensional Markov walk model with six states is proposed to characterize the dynamic behavior of the intercell movements for a mobile station. We discover a broad class of isotropic processes having an identical uniform steady-state distribution of the six directions, but distinct circulant transition probability matrices. Six special isotropic processes exhibiting IID, directional, turning, ping-pong, h-spin, and t-spin mobility patterns are identified for performance comparison. We also generalize the selective paging strategy by introducing the concept of probabilistic selective paging (PSP) to reduce the paging cost. A unified analysis using recursive computations is carried out to compute the exact probability distribution for the number of per-call location updates. We calculate the location profile with respect to an incoming call and derive an exact expression of the average paging cost for PSP. With its ability to distinguish subtle performance variations and unveil new features of various dynamic location management schemes, our analytic framework is demonstrated to provide more precise and insightful results than conventional analysis.
Some geometric applications using spreadsheets
Authors: David S. Tucker
Venue: Journal of Computing Sciences in Colleges (2002)

Ever since their invention, spreadsheets have been used by mathematics teachers to teach many mathematical concepts. As computer software and hardware capabilities have increased, developers have added many powerful new features to the spreadsheet program, especially in the area of graphics. When the Lotus Development Corporation developed SmartSuite 97, they added some features which make it possible to easily create certain learning applications in geometry. This paper explores two geometric applications. One is a visual model for shortest network applications which might be used in a discrete mathematics course or a contemporary mathematics course, and the other is a simple Geo board application which might be used in a course for elementary teachers. This second application takes advantage of special features of Lotus 1-2-3 97 (or Lotus 1-2-3 version 9.5)
From Ground Holding to Free Flight: An Exact Approach
Authors: Giovanni Andreatta, Lorenzo Brunetta, Guglielmo Guastalla
Venue: Transportation Science (2000)

Congestion in air traffic networks is a serious problem and has received a lot of attention both from the aviation authorities (Federal Aviation Administration, Eurocontrol, etc.) and from the scientific research community. In past years, one way of reducing the amount of congestion has been the adoption of ground holding policies, i.e., a ground hold is imposed to selected aircraft, prior to their departure, so that congestion may be smoothed away. Many airlines in the United States have been complaining about these policies and are pushing toward the new concept of "free flight," where the airlines are almost "free" to choose for each of their flights, when to depart, which route to follow, at what speed, etc., as long as the arrival at the destination airport matches a given time, decided by a central authority (the Federal Aviation Administration in the United States). In this new perspective, to avoid congestion, or at least to reduce it, the central authority has to schedule the arrival times of all flights, with possible delays for some of them. In this paper, we describe an exact algorithm, based on the integration of a heuristic algorithm with an integer linear programming model. This approach provides exact solutions in a much shorter computation time than previous algorithms proposed in the literature. We will report on our computational experiences using large instances based on actual Official Airline Guide data for the United States air traffic network.
The European IST ExPlanTech project
Authors: Adamantios Koumpis
Venue: Ubiquity (2001)

Hands-on adoption of a multi-agent production planning technology in the manufacturing industry.