ppxscal/embedding_network huggingface dataset:
Capacity Control for Partially Ordered Feature Sets
Authors: Ulrich Rückert
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II (2009)

Partially ordered feature sets appear naturally in many classification settings with structured input instances, for example, when the data instances are graphs and a feature tests whether a specific substructure occurs in the instance. Since such features are partially ordered according to an "is substructure of" relation, the information in those datasets is stored in an intrinsically redundant form. We investigate how this redundancy affects the capacity control behavior of linear classification methods. From a theoretical perspective, it can be shown that the capacity of this hypothesis class does not decrease for worst case distributions. However, if the data generating distribution assigns lower probabilities to instances in the lower levels of the hierarchy induced by the partial order, the capacity of the hypothesis class can be bounded by a smaller term. For itemset, subsequence and subtree features in particular, the capacity is finite even when an infinite number of features is present. We validate these results empirically on three graph datasets and show that the limited capacity of linear classifiers on such data makes underfitting rather than overfitting the more prominent capacity control problem. To avoid underfitting, we propose using more general substructure classes with "elastic edges" and we demonstrate how such broad feature classes can be used with large datasets.
Fast Co-clustering Using Matrix Decomposition
Authors: Yun Ling, Chongyi Ye
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

Co-clustering is a powerful data mining technique with varied applications such as text clustering, web-log mining and microarray analysis. Simultaneously clustering rows and columns (co-clustering) of large data matrix is an important problem with these wide applications. Current co-clustering techniques such as information-theoretic and Bayesian based methods provide good accuracy, but are computationally very expensive. Real data are noisy due to measurement technology limitation and experimental variability which prohibits co-clustering models from revealing true clusters corrupted by noise. Moreover, data matrices involving a large number of rows and columns limit their applicability. In this paper, we utilize correspondence analysis algorithm to process matrix decomposition and then make use of Bayesian approach for co-clustering. We find that utilizing the two methods synthetically is very significative to solve actual problems. Experiments on synthetic and real world data demonstrate the efficiency and effectiveness of our algorithm.
Treatment of &epsilon;-moves in subset construction
Authors: Gertjan van Noord
Venue: Proceedings of the International Workshop on Finite State Methods in Natural Language Processing (1998)

The paper discusses the problem of determinising finite-state automata containing large numbers of &epsilon;-moves. Experiments with finite-state approximations of natural language grammars often give rise to very large automata with a very large number of &epsilon;-moves. The paper identifies three subset construction algorithms which treat &epsilon;-moves. A number of experiments has been performed which indicate that the algorithms differ considerably in practice. Furthermore, the experiments suggest that the average number of &epsilon;-moves per state can be used to predict which algorithm is likely to perform best for a given input automaton.
Choosing the parameter of a modified additive-averaged splitting algorithm
Authors: V. A. Prusov, A. E. Doroshenko, R. I. Chernysh
Venue: Cybernetics and Systems Analysis (2009)

The problem-solving time and the solution accuracy are expressed as functions of a parameter. An optimization problem of choosing the parameter using a "time cost---solution accuracy" criterion is considered. A Pareto-optimal set of solutions is obtained. The best value of the parameter is chosen by the ideal-point method.
Lifetime Maximization Based on Coverage and Connectivity in Wireless Sensor Networks
Authors: Tong Zhao, Qing Zhao
Venue: Journal of Signal Processing Systems (2009)

We consider information retrieval in a wireless sensor network deployed to monitor a spatially correlated random field. We address optimal sensor scheduling and information routing under the performance measure of network lifetime. Both single-hop and multi-hop transmissions from sensors to an access point are considered. For both cases, we formulate the problems as integer programming based on the theories of coverage and connectivity in sensor networks. We derive upper bounds for the network lifetime that provide performance benchmarks for suboptimal solutions. Suboptimal sensor scheduling and data routing algorithms are proposed to approach the lifetime upper bounds with reduced complexity. In the proposed algorithms, we consider the impact of both the network geometry and the energy consumption in communications and relaying on the network lifetime. Simulation examples are used to demonstrate the performance of the proposed algorithms as compared to the lifetime upper bounds.
Phishing and Countermeasures in Spanish Online Banking
Authors: Ilkka Uusitalo, Josep M. Catot, Ramon Loureiro
Venue: Proceedings of the 2009 Third International Conference on Emerging Security Information, Systems and Technologies (2009)

This paper surveys the current situation of phishing attacks in Spain and discuss some of the currently used countermeasures. Based on specialist interviews we estimate the costs of phishing to both individual clients and the banks. The focus of this paper is on authentication and transaction signing methods. We give examples of ”two-factor”and ”two-factor, two-channel” authentication and transaction signing methods that are more resistant to phishing than the currently used username/password + coordinates card method. We consider the costs usability and security of these more robust methods.
A Data Mining Approach to Predicting Phylum for Microbial Organisms Using Genome-Wide Sequence Data
Authors: Rao M. Kotamarti, Douglas W. Raiford, Michael L. Raymer, Margaret H. Dunham
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Genomic sequencing projects are generating vast stores of data that provide opportunities and challenges in data analysis. Investigations of trends in codon usage have proven to be a rich area of study in this field. There are a number of methods for isolating codon usage bias in microbial organisms, each designed to capture a specific aspect of the bias. We posit that each species has evolved under the influence of a unique set of environmental constraints that has governed the shaping of the organism's codon usage. Analysis of codon usage data should, therefore, provide insights into the selection process at work influencing genomic composition. To this end, we describe the large-scale mining of genome-level data from several codon usage bias isolation techniques to determine whether this information can be used to predict the phylum and class to which each organism belongs. Successful prediction is an indication that the forces molding the codon usage of a given phylum/class are indeed distinctive, and that it would be of use in understanding the evolutionary forces involved. Additionally, it supports using this method to aid in, and validate existing taxonomic classification techniques.
The SpaTeC composite event language for spatio-temporal reasoning in mobile systems
Authors: Scarlet Schwiderski-Grosche, Ken Moody
Venue: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems (2009)

In mobile systems, the requirements on composite event detection are fundamentally different from those in distributed systems. Composite event detection must be driven not just by the time of occurrence of an event, but also by its location of occurrence; composite event detection, as applied in traditional distributed event-based systems, needs to be reassessed. In this paper, we motivate the need to support spatio-temporal relations between composite events in mobile systems and introduce SpaTeC, a composite event language that enables simultaneous matching of event occurrences over space and time. Composite event operators provide for coarse spatio-temporal reasoning. Spatial and temporal restrictions constrain composite event detection in space and time and provide a basis for event filtering and spatio-temporal routing. Time and location stamps use a guaranteed bounds model for location estimation and time synchronization. The semantics of SpaTeC event operators is defined within this framework.
User-extensible sequences in common Lisp
Authors: Christophe Rhodes
Venue: Proceedings of the 2007 International Lisp Conference (2007)

Common Lisp is often touted as the programmable programming language, yet it sometimes places large barriers in the way, with the best of intentions. One of those barriers is a limit to the extensibility by the user of certain core language constructs, such as the ability to define subclasses of built in classes usable with standard functions: even where this could be achievable with minimal penalties. We introduce the notion of user-extensible sequences, describing a protocol which implementations of such classes should follow. We show examples of their use, and discuss the issues observed in providing support for this protocol in a Common Lisp, including ensuring that there is no performance impact from its inclusion.
Smart Sensing Polymeric Foil with Integrated Optic Fiber Sensors: Fabrication and Characterization of a Polymeric Foil Sensitive to Strain
Authors: A. F. Silva, P. M. Mendes, J. H. Correia, F. Goncalves, L. A. Ferreira, F. M. Araujo
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

A structural integrity monitoring system based on optical fiber sensors is an important development at the smart structures level. However, direct sensors incorporation, without a substrate structure, creates some difficulties in eventual sensor maintenance or replacement. This paper presents an approach to overcome this issue. The fabrication, using industrial processes, and characterization of a polymeric foil able to sense, gather and send sensitive information for remote analysis is explored. The described example uses Fiber Bragg Grating sensors embedded in laminated polymeric sheets commonly used in different industries, as automotive, aeronautic, civil, among others. The fabricated foil is capable of transferring the full deformation to the optical sensor. The presented optical sensor incorporated in the polymeric foil is fully functional with high sensitivity, 0.6 picometer by microstrain, measuring deformation up to 1.2 millimeter. The sensors distribution over the structure is only restricted by the 10 mm sensor length, the desired dynamic range window and interrogation system used.
Sikuli: using GUI screenshots for search and automation
Authors: Tom Yeh, Tsung-Hsiang Chang, Robert C. Miller
Venue: Proceedings of the 22nd annual ACM symposium on User interface software and technology (2009)

We present Sikuli, a visual approach to search and automation of graphical user interfaces using screenshots. Sikuli allows users to take a screenshot of a GUI element (such as a toolbar button, icon, or dialog box) and query a help system using the screenshot instead of the element's name. Sikuli also provides a visual scripting API for automating GUI interactions, using screenshot patterns to direct mouse and keyboard events. We report a web-based user study showing that searching by screenshot is easy to learn and faster to specify than keywords. We also demonstrate several automation tasks suitable for visual scripting, such as map navigation and bus tracking, and show how visual scripting can improve interactive help systems previously proposed in the literature.
Software for Petascale Computing Systems
Authors: William D. Gropp
Venue: IEEE Design Test (2009)

Developing software for highly scalable systems with nearly a million processors or cores raises unique challenges. To succeed, application developers must reconsider both their code's structure and the tools they use to develop, tune, and run that code.
Image Reconstruction Using an Improved MAP-EM Method in X-ray CT
Authors: Baoyu Dong
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

An improved MAP-EM algorithm is proposed for Bayesian reconstruction in X-ray CT based upon Markov random field priors and the Poisson data model. The improved algorithm can yield better reconstruction than MAP-EM algorithm, and its convergence is faster. The improved method is verified by applications to computer simulation data and real X-ray CT data from two aluminous tubes scans. Experiments results show this method is effective. Reconstructed slice images of the improved algorithm are accurate and clear.
Learning from multiple heuristics
Authors: Mehdi Samadi, Ariel Felner, Jonathan Schaeffer
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

Heuristic functions for single-agent search applications estimate the cost of the optimal solution. When multiple heuristics exist, taking their maximum is an effective way to combine them. A new technique is introduced for combining multiple heuristic values. Inspired by the evaluation functions used in two-player games, the different heuristics in a single-agent application are treated as features of the problem domain. An ANN is used to combine these features into a single heuristic value. This idea has been implemented for the sliding-tile puzzle and the 4-peg Towers of Hanoi, two classic single-agent search domains. Experimental results show that this technique can lead to a large reduction in the search effort at a small cost in the quality of the solution obtained.
On the Complexity of Semantic Self-minimization
Authors: Adam Antonik, Michael Huth
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Partial Kripke structures model only parts of a state space and so enable aggressive abstraction of systems prior to verifying them with respect to a formula of temporal logic. This partiality of models means that verifications may reply with true (all refinements satisfy the formula under check), false (no refinement satisfies the formula under check) or don't know. Generalized model checking is the most precise verification for such models (all don't know answers imply that some refinements satisfy the formula, some don't), but computationally expensive. A compositional model-checking algorithm for partial Kripke structures is efficient, sound (all answers true and false are truthful), but may lose precision by answering don't know instead of a factual true or false. Recent work has shown that such a loss of precision does not occur for this compositional algorithm for most practically relevant patterns of temporal logic formulas. Formulas that never lose precision in this manner are called semantically self-minimizing. In this paper we provide a systematic study of the complexity of deciding whether a formula of propositional logic, propositional modal logic or the propositional modal mu-calculus is semantically self-minimizing.
RBF Neural Network Control and Novel Smith Predictor for Networked Control Systems
Authors: Feng Du, Wencai Du
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

This paper aims to the random and uncertain network delays, a novel approach is proposed that new Smith predictor combined with adaptive PID control with RBF neural network for networked control systems (NCS). This novel Smith predictor comes true to hide predictor models of the network delays into real network data transmission processes, therefore network delays don’t need to be measured, identified or estimated on-line. Based on CSMA/CD (Ethernet), the results of simulation show validity of this control scheme, and indicate that system has better dynamic performance and strong robustness.
Prefetching Optimization in P2P VoD Applications
Authors: Yifeng He, Ling Guan
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

Most existing Peer-to-Peer (P2P) Video-on-Demand (VoD) systems have been designed and optimized for the sequential playback. In practice, users often want to seek to the positions they are interested in. Such frequent seeks raise a great challenge to the design of the prefetching scheme. In this paper, we propose an optimal prefetching scheme to minimize the expected seeking delay at every viewing position. The proposed prefetching scheme optimally determines which segments will be prefetched and cached, based on the segment access probability. Through extensive simulations, we demonstrate that the proposed prefetching scheme significantly reduces the seeking delay compared to the sequential prefetching scheme.
Context-Dependent Personalised Feedback Prioritisation in Exploratory Learning for Mathematical Generalisation
Authors: Mihaela Cocea, George Magoulas
Venue: Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH (2009)

In this paper we address the problem of prioritising feedback on the basis of multiple heterogeneous pieces of information in exploratory learning. The problem arises when multiple types of feedback are required in order to address different types of conceptual difficulties, accommodate particular learning behaviours identified during exploration, and provide appropriate support depending on the learning mode (e.g. individual or collaborative learning) and/or the stage of the exploratory learning process. We propose an approach that integrates learners' characteristics and context-related information through a Multicriteria Decision-Making formalism. The outcome is a context-aware mechanism for prioritising personalised feedback that is tested in an exploratory learning environment for mathematical generalisation.
Hypergraphs, Characteristic Polynomials and the Ihara Zeta Function
Authors: Peng Ren, Tatjana Aleksić, Richard C. Wilson, Edwin R. Hancock
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

In this paper we make a characteristic polynomial analysis on hypergraphs for the purpose of clustering. Our starting point is the Ihara zeta function [8] which captures the cycle structure for hypergraphs. The Ihara zeta function for a hypergraph can be expressed in a determinant form as the reciprocal of the characteristic polynomial of the adjacency matrix for a transformed graph representation. Our hypergraph characterization is based on the coefficients of the characteristic polynomial, and can be used to construct feature vectors for hypergraphs. In the experimental evaluation, we demonstrate the effectiveness of the proposed characterization for clustering hypergraphs. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Instant Online Communities as a Means to Foster Conferences
Authors: Martin Christof Kindsmüller, Jan Milz, Johannes Schmidt
Venue: Proceedings of the 3d International Conference on Online Communities and Social Computing: Held as Part of HCI International 2009 (2009)

In this paper we introduce an instant online community (IOC) solution as an add-on for existing websites. The IOC enables social interaction between the main content provider and visitors of one or more websites. We present the successful application of the sixgroups.com Livecommunity in the context of a joint conference to support communication between organizers and attendees, and attendees amongst each others. All stakeholders are supported throughout the conference, from preparation until follow-up. Yet, the main focus lies in accompanying them while they are attending the conference. The lessons learned and conclusions from this application are discussed, as well as the steps to be taken in improving the sixgroups.com Livecommunity.
Extractors for Varieties
Authors: Zeev Dvir
Venue: Proceedings of the 2009 24th Annual IEEE Conference on Computational Complexity (2009)

We study the task of randomness extraction from sources which are distributed uniformly on an unknown algebraic variety. In other words, we are interested in constructing a function (an extractor) whose output is close to uniform even if the input is drawn uniformly from the set of solutions of an unknown system of low degree polynomials. This problem generalizes the problem of extraction from affine sources which has drawn a considerable amount of interest lately. We present two constructions of explicit extractors for varieties. The first works for varieties of any size (including one dimensional varieties, or curves) and requires field size which is exponential in the overall dimension of the space. Our second extractor allows the field size to be polynomial in the degree of the equations defining the variety, but works only for varieties whose size is at least the square root of the total size of the space.
Feature-Driven and Incremental Variability Generalization in Software Product Line
Authors: Liwei Shen, Xin Peng, Wenyun Zhao
Venue: Proceedings of the 11th International Conference on Software Reuse: Formal Foundations of Reuse and Domain Engineering (2009)

In the lifecycle of a software product line (SPL), incremental generalization is usually required to extend the variability of existing core assets to support the new or changed application requirements. In addition, the generalization should conform to the evolved SPL requirements which are usually represented by a feature model. In this paper, we propose a feature-driven and incremental variability generalization method based on the aspect-oriented variability implementation techniques. It addresses a set of basic scenarios where program-level JBoss-AOP based reference implementations respond to the feature-level variability generalization patterns. It also provides the corresponding guidance to compose these patterns in more complex cases. Based on the method, we present a case study and related discussions.
Driving Stability of Closed Loop Tractor-Semitrailer Vehicle System with Optimal Driver Model
Authors: Xian-sheng Li, Jian-guo Zhang, Meng-yao Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

A quasi-linear driver model was developed, and a closed loop tractor-semitrailer vehicle system composed of the driver model and a tractor-semitrailer vehicle model of 3-degrees-of-freedom were proposed. The stability of closed loop vehicle system was studied by simulating the system with different parameter values. A roots-locating numerical method was used to identify critical speed of the system. Some simulation of closed loop vehicle system were made in Matlab and the results shown that driver's inherent time delay, a semitrailer's load and driving speed make important role in stability of closed loop tractor-semi trailer.