ppxscal/embedding_network huggingface dataset:
Catching the Drift: Using Feature-Free Case-Based Reasoning for Spam Filtering
Authors: Sarah Jane Delany, Derek Bridge
Venue: Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development (2007)

In this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam filter that uses a feature-free distance measure based on text compression. In our experiments, we compare two ways to normalise such a distance measure, finding that the one proposed in [1] performs better. We show that a policy as simple as retaining misclassified examples has a hugely beneficial effect on handling concept drift in spam but, on its own, it results in the case base growing by over 30%. We then compare two different retention policies and two different forgetting policies (one a form of instance selection, the other a form of instance weighting) and find that they perform roughly as well as each other while keeping the case base size constant. Finally, we compare a feature-based textual case-based spam filter with our feature-free approach. In the face of concept drift, the feature-based approach requires the case base to be rebuilt periodically so that we can select a new feature set that better predicts the target concept. We find feature-free approaches to have lower error rates than their feature-based equivalents.
Nonhomogeneous boundary value problem for first-order impulsive differential equations with delay
Authors: Fengqin Zhang, Meili Li, Jurang Yan
Venue: Computers Mathematics with Applications (2006)

The authors employ the method of upper and lower solution coupled with the monotone iterative technique to obtain results of existence and uniqueness for a nonhomogeneous boundary value problem of impulsive differential equations with delay.
Image Quality Measurements in Breast Tomosynthesis
Authors: Ruben Engen, Ramona Bouwman, Roeland Burght, Barbara Lazzari, David R. Dance, Patrice Heid, Magnus Aslund, Kenneth C. Young
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Breast tomosynthesis systems are developed by a number of manufacturers. It is desirable to have methods for image quality evaluation that can be used for quality control and minimum performance. In this study methods of measurement of three aspects of image quality (homogeneity, artifacts and detail detection on a homogeneous background) are evaluated on a prototype tomosynthesis system. The homogeneity evaluation showed that pixel value and standard deviation varied by up to respectively 6% and 30% in the tomosynthesis image. Artifacts have been quantified using an aluminium sphere of 2 mm diameter. In the plane of the object higher pixel value artefacts were visible. In all other planes artefacts were also visible. The detail detection did not fulfil the limiting values of threshold contrast for projection mammography, but image quality might have been underestimated. Homogeneity, detail detection and artifacts should be evaluated in future quality control procedures for tomosynthesis.
An Integer Programming Algorithm for Routing Optimization in IP Networks
Authors: Andreas Bley
Venue: Proceedings of the 16th annual European symposium on Algorithms (2008)

Most data networks nowadays use shortest path protocols to route the traffic. Given administrative routing lengths for the links of the network, all data packets are sent along shortest paths with respect to these lengths from their source to their destination.In this paper, we present an integer programming algorithm for the minimum congestion unsplittable shortest path routing problem, which arises in the operational planning of such networks. Given a capacitated directed graph and a set of communication demands, the goal is to find routing lengths that define a unique shortest path for each demand and minimize the maximum congestion over all links in the resulting routing. We illustrate the general decomposition approach our algorithm is based on, present the integer and linear programming models used to solve the master and the client problem, and discuss the most important implementational aspects. Finally, we report computational results for various benchmark problems, which demonstrate the efficiency of our algorithm.
Using Disparity to Enhance Test Generation for Hybrid Systems
Authors: Thao Dang, Tarik Nahhal
Venue: Proceedings of the 20th IFIP TC 6/WG 6.1 international conference on Testing of Software and Communicating Systems: 8th International Workshop (2008)

This paper deals with the problem of test generation for hybrid systems, which are systems with mixed discrete and continuous dynamics. In our previous work [9], we developed a coverage guided test generation algorithm, inspired by a probabilistic motion planning technique. The algorithm is guided via a process of sampling goal states, which indicate the directions to steer the system towards. In this paper, we pursue this work further and propose a method to enhance coverage quality by introducing a new notion of disparity. This notion is used to predict the situations where the goal states can not be `directly' reached. We then develop an adaptive sampling method which permits improving coverage quality. This method was implemented and successfully applied to a number of case studies in analog and mixed-signal circuits, a domain where hybrid systems can be used as an appropriate high level model.
A Ring Model for the Development of Simple Cells in the Visual Cortex
Authors: Takashi Hamada, Kazuhiro Okada
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

A model was proposed for the development of simple receptive fields in the cat visual cortex, based on the empirical evidence that the development is due to dark or spontaneous activities in the lateral geniculate nucleus (LGN). We assumed that several cortical cells are arranged in a ring, with mutual excitatory and inhibitory connections of fixed weights; The cells also receive excitatory synapses from LGN cells, whose synaptic weights are initially set to be random and then modified according to the Hebb rule as well as to positive correlations among nearby LGN cells. Computer simulation showed that the cortical cells finally acquire two-dimensional simple receptive fields with their phases gradually varied along the ring.
On Problems without Polynomial Kernels (Extended Abstract)
Authors: Hans L. Bodlaender, Rodney G. Downey, Michael R. Fellows, Danny Hermelin
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

Kernelization is a central technique used in parameterized algorithms, and in other approaches for coping with NP-hard problems. In this paper, we introduce a new method which allows us to show that many problems do not have polynomial size kernels under reasonable complexity-theoretic assumptions. These problems include k -Path, k -Cycle, k -Exact Cycle, k -Short Cheap Tour, k -Graph Minor Order Test, k -Cutwidth, k -Search Number, k -Pathwidth, k -Treewidth, k -Branchwidth, and several optimization problems parameterized by treewidth or cliquewidth.
A Discrete-Logarithm Based Non-interactive Non-malleable Commitment Scheme with an Online Knowledge Extractor
Authors: Ning Ding, Dawu Gu
Venue: Information Security and Cryptology: Third SKLOIS Conference, Inscrypt 2007, Xining, China, August 31 - September 5, 2007, Revised Selected Papers (2007)

We propose a discrete-logarithm based non-interactive non-malleable commitment scheme with an online knowledge extractor in the random oracle and the public parameter model (need a third party to distribute public parameters to both sender and receiver in advance). Our scheme is statistically-secret computationally-binding. The fundamental technique we employ is the construction of non-interactive zero-knowledge proofs of knowledge with online knowledge extractors from Fiat-Shamir proofs of knowledge for relations with logarithmic challenge length presented by Fischlin in Crypto'05. Compared with previous works, our scheme is practical and the online knowledge extractor is strictly polynomial-time.
The Limitations of Frequency Analysis for Dendritic Cell Population Modelling
Authors: Robert Oates, Graham Kendall, Jonathan M. Garibaldi
Venue: Proceedings of the 7th international conference on Artificial Immune Systems (2008)

In previous work we derived a mathematical model which allows the frequency response of a dendritic cell to be predicted. The model has three, key limitations: the model assumes that the intermediate co stimulatory molecule signal is constant; it is only possible to make predictions for a single cell and the model only takes into account the signal processing element of the dendritic cell algorithm, with no attempt to explore the antigen presenting phase. In this paper we explore the original model and attempt to extend it to include the effects of multiple cells. It is found that the complex interactions between the cells creates a one to many relationship between the input frequency and the output frequency. This suggests that traditional frequency-based techniques alone are unlikely to yield an effective automated tuning mechanism.
Detection of Clustered Microcalcifications with SUSAN Edge Detector, Adaptive Contrast Thresholding and Spatial Filters
Authors: G. Veni, E. E. Regentova, L. Zhang
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

Clustered microcalcifications (MCs) are detected in digital mammograms using SUSAN edge detector and adaptive contrast thresholding technique. MC clusters are found using spatial filters. Based on that a computer aided diagnostic prompting system is developed which achieves 97.4 % of true positive clusters at very low false positive rates according to the trial of 100 patches with the signs of both benign and malignant nature taken from the DDSM database mammograms
An overview of the OMNeT++ simulation environment
Authors: András Varga, Rudolf Hornig
Venue: Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops (2008)

The OMNeT++ discrete event simulation environment has been publicly available since 1997. It has been created with the simulation of communication networks, multiprocessors and other distributed systems in mind as application area, but instead of building a specialized simulator, OMNeT++ was designed to be as general as possible. Since then, the idea has proven to work, and OMNeT++ has been used in numerous domains from queuing network simulations to wireless and ad-hoc network simulations, from business process simulation to peer-to-peer network, optical switch and storage area network simulations. This paper presents an overview of the OMNeT++ framework, recent challenges brought about by the growing amount and complexity of third party simulation models, and the solutions we introduce in the next major revision of the simulation framework.
Principal Component Analysis for Sparse High-Dimensional Data
Authors: Tapani Raiko, Alexander Ilin, Juha Karhunen
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solving PCA, but a number of other algorithms have been proposed. For instance, the EM algorithm is much more efficient in case of high dimensionality and a small number of principal components. We study a case where the data are high-dimensional and a majority of the values are missing. In this case, both of these algorithms turn out to be inadequate. We propose using a gradient descent algorithm inspired by Oja's rule, and speeding it up by an approximate Newton's method. The computational complexity of the proposed method is linear with respect to the number of observed values in the data and to the number of principal components. In the experiments with Netflix data, the proposed algorithm is about ten times faster than any of the four comparison methods.
The Ackermann Award 2007
Authors: Martin Grohe, Martin Hyland, Johann A. Makowsky, Damian Niwinski
Venue: Proceedings of the 21st international workshop and the 16th Annual Conference of the EACSL on Computer Science Logic (2007)

The third Ackermann Award is presented at this CSL'07. This is the first year in which the EACSL Ackermann Award is generously sponsored. Our sponsor for the next three years is the worlds leading provider of personal peripherals, Logitech S.A., situated in Romanel, Switzerland.
Support Vector Machines and Genetic Algorithms for Soft-Sensing Modeling
Authors: Sang Haifeng, Yuan Weiqi, Wang Fuli, He Dakuo
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III (2007)

Soft sensors have been widely used in industrial process control to improve the quality of product and assure safety in production. This paper introduces support vector machines (SVM) into soft-sensing modeling. Building the models, on one hand we want to have the best set of input variables, on the other hand we want to get the best possible performance of the SVM model. So the Genetic Algorithms is used to choose the input variables and select the parameters of SVM. Moreover, training the model on data coming a real experiment process--Nosiheptide fermentation process and evaluating the model performance on the same process. Results show that SVM model optimized by Genetic Algorithms provides a new and effective method for soft- sensing modeling and has promising application in industrial process applications.
Efficient texture synthesis using strict Wang Tiles
Authors: Xinyu Zhang, Young J. Kim
Venue: Graphical Models (2008)

Wang Tiles are constructed from four texture samples, arranged so they can always match a choice of other tiles at two edges. Because they are precomputed, Wang Tiles are a very efficient way to generate textures on the fly. But matching problems occur within tiles and at the corners of adjacent tiles. By replacing the edge-matching texture samples with a new sample in the center of the tile, and using the graph cut path-finding algorithm, we overcome these problems and introduce additional texture diversity. Our s-Wang Tiles are a stricter interpretation of the original Wang Tile design, and our tile set is also smaller than that required by @w-Tiles: only eight different tiles are required for a non-repetitive titling.
Aligning social welfare and agent preferences to alleviate traffic congestion
Authors: Kagan Tumer, Zachary T Welch, Adrian Agogino
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Multiagent coordination algorithms provide unique insights into the challenging problem of alleviating traffic congestion. What is particularly interesting in this class of problem is that no individual action (e.g., leave at a given time) is intrinsically "bad" but that combinations of actions among agents lead to undesirable outcomes. As a consequence, agents need to learn how to coordinate their actions with those of other agents, rather than learn a particular set of "good" actions. In general, the traffic problem can be approached from two distinct perspectives: (i) from a city manager's point of view, where the aim is to optimize a city wide objective function (e.g., minimize total city wide delays), and (ii) from the individual driver's point of view, where each driver is aiming to optimize a personal objective function (e.g., a "timeliness" function that minimizes the difference desired and actual arrival times at a destination). In many cases, these two objective functions are at odds with one another, where drivers aiming to optimize their own objectives yield to congestion and poor values of city objective functions. In this paper we present an objective shaping approach to both types of problems and study the system behavior that arises from the drivers' choices. We first show a topdown approach that provides incentives to drivers and leads to good values of the city manager's objective function. We then present a bottom-up approach that shows that drivers aiming to optimize their own personal timeliness objective lead to poor performance with respect to a city manager's objective function. Finally, we present the intriguing result that drivers that aim to optimize a modified version of their own timeliness function not only perform well in terms of the city manager's objective function, but also perform better with respect to their own original timeliness functions.
Codes from Expander Graphs
Authors: Tom Høholdt
Venue: Proceedings of the 2nd international Castle meeting on Coding Theory and Applications (2008)

We survey some recent work on codes based on bipartite expander graphs. The code symbols are associated with the branches and the symbols connected to a given node are restricted to be codewords in certain constituent codes (e.g. Reed---Solomon codes). This class turn out to contain some exellent codes. We give results on the parameters of the codes and methods for their encoding. We also analyze the performance under iterative decoding, partly based on a result on cores in random graphs.
A Kernel Method for the Optimization of the Margin Distribution
Authors: Fabio Aiolli, Giovanni San Martino, Alessandro Sperduti
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

Recent results in theoretical machine learning seem to suggest that nice properties of the margin distribution over a training set turns out in a good performance of a classifier. The same principle has been already used in SVM and other kernel based methods as the associated optimization problems try to maximize the minimum of these margins.In this paper, we propose a kernel based method for the direct optimization of the margin distribution (KM-OMD). The method is motivated and analyzed from a game theoretical perspective. A quite efficient optimization algorithm is then proposed. Experimental results over a standard benchmark of 13 datasets have clearly shown state-of-the-art performances.
A3: a coding guideline for HCI+autism research using video annotation
Authors: Joshua Hailpern, Karrie Karahalios, James Halle, Laura DeThorne, Mary-Kelsey Coletto
Venue: Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility (2008)

Due to the profile of strengths and weaknesses indicative of autism spectrum disorders (ASD), technology may play a key role in ameliorating communication difficulties with this population. This paper documents coding guidelines established through cross-disciplinary work focused on facilitating communication development in children with ASD using computerized feedback. The guidelines, referred to as A3 (pronounced A-Cubed) or Annotation for ASD Analysis, define and operationalize a set of dependent variables coded via video annotation. Inter-rater reliability data are also presented from a study currently in-progress, as well as related discussion to help guide future work in this area. The design of the A3 methodology is well-suited for the examination and evaluation of the behavior of low-functioning subjects with ASD who interact with technology.
Optimization Algorithm and Data Security Problem in Distributed Information Systems
Authors: Agnieszka Dardzinska-Glebocka
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

In this work we present a new rule-discovery method for Distributed Information System. DIS is the system that connects a number of information systems using network communication technology. This communication can be driven by request for knowledge needed to predict for maximal optimization which missing values can be replaced. In this work we recall the notion of a distributed information system to talk about handling semantic inconsistencies between sites. Semantic inconsistencies are due to different interpretations of attributes and their values on the concepts level among sites. Different interpretations can be also linked with a different way of treating null values among sites. Some attributes might be just hidden because of the security reason. In such case we have to be certain that the missing data can not be reconstructed from the available data by any known null value imputation method and that some information in IS can not be uncovered as well. Assuming that one attribute is hidden at one of the sites of DIS we will try to reconstruct this attribute. In this paper we will also show which values have to be hidden from users to guarantee that the hidden attribute can not be reconstructed.
Abstract Interpretation with Applications to Timing Validation
Authors: Reinhard Wilhelm, Björn Wachter
Venue: Proceedings of the 20th international conference on Computer Aided Verification (2008)

Abstract interpretation is one of the main verification technologies besides model checking and deductive verification.Abstract interpretation has a rich theory of abstraction and strong support for the construction of abstract domains. It allows to express a precise relation to the (concrete) semantics of the programming language inducing a clear relation between the results of an abstract interpretation and the properties of the analyzed program. It permits trading efficiency against precision and offers means to enforce termination where this is not guaranteed.We explain abstract interpretation using examples from a particular application domain: the determination of bounds on the execution times of programs. These bounds are used to show reliably that hard real-time systems satisfy their timing constraints.The application domain requires a number of static analyses and domains with different characteristics. Most domains exhibit Galois connections, a few do not. Some analyses require widening to leap infinite ascending chains and ensure termination.
Evaluation of P2P Algorithms for Probabilistic Trust Inference in a Web of Trust
Authors: Huqiu Zhang, Aad Moorsel
Venue: Proceedings of the 5th European Performance Engineering Workshop on Computer Performance Engineering (2008)

The problem of finding trust paths and estimating the trust one can place in a partner arises in various application areas, including virtual organisations, authentication systems and reputation systems. We study the use of peer-to-peer algorithms for finding trust paths and probabilistically assessing trust values in systems where trust is organised similar to the `web of trust'. We do this through discrete event simulation of random as well as scale free trust networks based on flooding as well as selective search algorithms. Our main conclusion is that in many situations these algorithms can be seen as belonging to a single class of algorithms that perform equally, and only differ through (and are sensitive to) parameter choices. We will also see that flooding is the only applicable method if one stresses the requirement for finding all trust paths, and if networks are less connected.