ppxscal/embedding_network huggingface dataset:
Reliable face recognition using adaptive and robust correlation filters
Authors: Hung Lai, Venkatesh Ramanathan, Harry Wechsler
Venue: Computer Vision and Image Understanding (2008)

This paper expands on the scope of correlation filters to show their usefulness for reliable face recognition. Towards that end we propose adaptive and robust correlation filters (ARCF) and describe their usefulness for reliable face authentication using recognition-by-parts strategies. ARCF provide information that involves both appearance and location. The cluster and strength of the ARCF correlation peaks indicate the confidence of the face authentication made, if any. The development of ARCF, motivated by MACE filters and adaptive beam-forming from radar/sonar, is driven by Tikhonov regularization. The adaptive aspect of ARCF comes from their derivation using both training and test data, similar to transduction, while the robust aspect benefits from the correlation peak optimization to decrease their sensitivity to noise and distortions. The comparative advantages of ARCF are motivated, explained, and illustrated vis-a-vis competing correlation filters. Experimental evidence shows the feasibility and reliability of ARCF vis-a-vis occlusion, disguise, and illumination, expression, and temporal variability. The generalization ability of ARCF is further illustrated when decision-making thresholds learned a priori from one data base, e.g., FERET, carry over to face images from another data base, e.g., AR.
Quantitative Risk Analysis and Evaluation in Information Systems: A Case Study
Authors: Young-Gab Kim, Jongin Lim
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

The rapid growth of the Internet technology has encouraged organizations to protect their information assets. Furthermore, the need for risk analysis has become very important for organizations. However, the existing risk analysis just presents the guidelines that can be used to determine the security measures but do not support how to evaluate the risks quantitatively. Therefore, in this paper, the quantitative risk evaluation model based on the Markov process, especially for the case of interrelated threats, is proposed. In addition, in order to analyze the relationship between threats, the basic analysis method using the covariance and the correlation coefficient is presented.
Application of chaotic dynamics in a recurrent neural network to control: hardware implementation into a novel autonomous roving robot
Authors: Yongtao Li, Shuhei Kurata, Shogo Morita, So Shimizu, Daigo Munetaka, Shigetoshi Nara
Venue: Biological Cybernetics (2008)

Originating from a viewpoint that complex/chaotic dynamics would play an important role in biological system including brains, chaotic dynamics introduced in a recurrent neural network was applied to control. The results of computer experiment was successfully implemented into a novel autonomous roving robot, which can only catch rough target information with uncertainty by a few sensors. It was employed to solve practical two-dimensional mazes using adaptive neural dynamics generated by the recurrent neural network in which four prototype simple motions are embedded. Adaptive switching of a system parameter in the neural network results in stationary motion or chaotic motion depending on dynamical situations. The results of hardware implementation and practical experiment using it show that, in given two-dimensional mazes, the robot can successfully avoid obstacles and reach the target. Therefore, we believe that chaotic dynamics has novel potential capability in controlling, and could be utilized to practical engineering application.
Quantile regression for binary performance indicators
Authors: Paul Hewson, Keming Yu
Venue: Applied Stochastic Models in Business and Industry (2008)

Quantile regression is an emerging modelling technique; we examine an approach allowing this technique to model binomial variables in a Bayesian framework and illustrate the value of this advanced technique on a set of local government performance indicators from England and Wales. In U.K. local government, there is currently particular interest in assessing performance relative to &lsquo;top&rsquo; and &lsquo;bottom&rsquo; quartiles; all authorities are expected to match the current best quartile performance within 5 years, any authority in the &lsquo;bottom&rsquo; quartile is assumed to be significantly below par. By its very nature, quantile regression lets us to explore relationships between various covariates and these particular levels of performance. Additionally, by examining a number of other percentiles, we demonstrate how quantile regression gives a much fuller insight into the apparent behaviour of the system we are modelling. Rather than relying on asymptotic results, we use Bayesian methods that allow us to explore the uncertainty implicit in our model building and predictions. We suggest that this is most important when analysing data that are used to make managerial and administrative decisions. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Searching for Better Randomized Response Schemes for Privacy-Preserving Data Mining
Authors: Zhengli Huang, Wenliang Du, Zhouxuan Teng
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

To preserve user privacy in Privacy-Preserving Data Mining (PPDM), the randomized response (RR) technique is widely used for categorical data. Although various RR schemes have been proposed, there is no study to systematically compare them in order to find optimal RR schemes. In the paper, we choose the R-U (Risk-Utility) confidentiality map to compare different randomization schemes. Using the R-U map as our metric, we present an optimal RR scheme for binary data, which helps us find an optimal class of RR matrices. From this optimal scheme, we have discovered several heuristic rules among the elements in the optimal class. We generalize these rules to find optimal class of RR matrices for categorical data. Based on these rules, we propose an RR scheme to find a class of RR matrices for categorical data. Our experimental results have shown that our scheme has much better performance than the existing RR schemes.
A Semantics-Based Dialogue for Interoperability of User-Adaptive Systems in a Ubiquitous Environment
Authors: Federica Cena, Lora M. Aroyo
Venue: Proceedings of the 11th international conference on User Modeling (2007)

In this paper we present an approach to enable interoperability of user-adaptive systems (UASs) in a ubiquitous environment. We model the interactions between systems as a semantics-based dialogue for exchanging user model and context data. We focus on the user data clarification and negotiation tasks, and show how semantics enables, on the one hand, the understanding among user-adaptive systems in a distributed ubiquitous setting, and on the other hand indirectly improves their effectiveness in producing end user results. We deploy and evaluate our approach in the UbiquiTO mobile adaptive tourist guide.
Discovering Relational Emerging Patterns
Authors: Annalisa Appice, Michelangelo Ceci, Carlo Malgieri, Donato Malerba
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

The discovery of emerging patterns (EPs) is a descriptive data mining task defined for pre-classified data. It aims at detecting patterns which contrast two classes and has been extensively investigated for attribute-value representations. In this work we propose a method, named Mr-EP, which discovers EPs from data scattered in multiple tables of a relational database. Generated EPs can capture the differences between objects of two classes which involve properties possibly spanned in separate data tables. We implemented Mr-EP in a pre-existing multi-relational data mining system which is tightly integrated with a relational DBMS, and then we tested it on two sets of geo-referenced data.
Peeling the 802.11 onion: separating congestion from physical per
Authors: Malik Ahmad Yar Khan, Darryl Veitch
Venue: Proceedings of the third ACM international workshop on Wireless network testbeds, experimental evaluation and characterization (2008)

An ability to accurately classify observed packet errors according to their root cause: physical layer or MAC layer contention, in 802.11 networks, opens up many opportunities for performance improvement at the both the MAC and IP layers. We investigate two orthogonal ways to achieve this, and present a methodology, the 'map', for clearly visualizing the results free of packet size and rate 'bias'.
XOS-SSH: a lightweight user-centric tool to support remote execution in virtual organizations
Authors: An Qin, Haiyan Yu, Chengchun Shu, Bing Xu
Venue: First USENIX Workshop on Large-Scale Computing (2008)

Large-scale virtual organizations (VOs) often comprise resource providers from different administrative domains, each probably with a specific security model. Grids try to solve this problem by providing a new security infrastructure featured with single-sign on (SSO). However, the usability of Grids is often impaired by the complexity of configuring and maintaining the new security infrastructure as well as adapting to new interfaces of security enabled services. The co-existing of different Grid platforms and SSO solutions among resource providers makes this situation even worse. In this paper, we present XOS-SSH, a lightweight user-centric tool to support remote execution of jobs among heterogeneous nodes of VOs. XOS-SSH is a modified version of the widely used OpenSSH tool based on several OS-level VO support mechanisms developed in XtreemOS project [23]. XOS-SSH adopts a pluggable framework that is capable of supporting different authentication schemes and making them transparent to shell users. The performance evaluation of XOS-SSH around NAS Parallel Benchmarks (NPB) shows that our current implementation incurs trivial overhead comparing to the unmodified one.
Graphical Revelations: Comparing Students' Translation Errors in Graphics and Logic
Authors: Richard Cox, Robert Dale, John Etchemendy, Dave Barker-Plummer
Venue: Proceedings of the 5th international conference on Diagrammatic Representation and Inference (2008)

We are interested in developing a better understanding of what it is that students find difficult in learning logic. We use both natural language and diagram-based methods for teaching students the formal language of first-order logic. In this paper, we present some initial results that demonstrate that, when we look at how students construct diagrammatic representations of information expressed in natural language (nl) sentences, the error patterns are different from those observed when students translate from nl to first-order logic (fol). In the nl-to-diagram construction task, errors associated with the interpretation of the expression not a small dodecahedron were manifested much more frequently with respect to the object's size than with respect to its shape. In the nl-to-fol task, however, no such asymmetry was observed. We hypothesize a number of possible factors that might be implicated here: differences between the nl-to-diagram and nl-to-fol tasks; the reduced expressivity of diagrams compared to language; scoping errors in participants' nl parsing; and the visuospatial properties of the blocks-world domain. In sum, constructing a diagram requires the student to provide an instantiated representation of the meaning of a natural language sentence; this tests their understanding in a way that translation into first-order logic does not, by ensuring that they are not simply carrying out a symbol manipulation exercise.
Algorithms for bandit online linear optimization
Authors: Lance Fortnow
Venue:  (2008)

The well-known "multi-armed bandit" problem is a problem of iterated decision making in a largely unknown and constantly changing environment. A decision-maker must repeatedly select one of k decisions, and incur a corresponding loss, with the eventual goal of minimizing the "regret," defined as the difference between the actual total loss of an online decision-making procedure and that of the best single decision in hindsight. This problem has been well studied, and the best algorithms achieve the optimal regret of kT (ignoring polylogarithmic factors), where T is the number of rounds for which the game is played. We study the problem of "bandit online linear optimization," which is a generalization of the multi-armed bandit problem to a setting in which the decision set is a compact subset of Rn and the loss functions to be optimized are linear. Although the algorithms from the multi-armed bandit setting can be directly applied here, they suffer from the dependence of their regret on the size of the decision set, since this may be very large or even infinite. The aim, rather, is to find algorithms whose regret is controlled by the ambient dimension n. "Bandit" refers to the setting in which the algorithm is only told its loss on each round, rather than the entire loss function. Prior to our work, algorithms for the bandit setting with bounded linear loss functions, achieved a regret bound that was polynomial in n by sacrificing their dependence on the number of rounds, the best previous bounds being of order poly(n)T2/3. We bridge this gap by presenting an algorithm that has expected regret at most n3/2 T (ignoring polylogarithmic factors). We also present a modification of our algorithm which achieves the same regret bound with high probability. We provide lower bounds to show that no algorithm for bandit online linear optimization can achieve lower regret than &Omega;(n T ). An easy corollary of earlier work of Freund and Schapire shows that in the full-information setting, (i.e., when the algorithm observes the entire loss vector each round) a regret bound of O( nT ) is possible. Thus we show that for online linear optimization, the price of bandit information, i.e., the extra regret factor due to not observing the entire loss function is between n and n. Another variant of the problem has the loss functions drawn from some fixed but unknown distribution. For this case we present a deterministic algorithm which achieves a regret of O(n T ) in general. In the special case when the decision set is a fixed polytope, this algorithm achieves regret O(n 2 log3 T). We also give a lower bound of &Omega;( nT ) on regret for general compact decision sets.
Interval Self-Organizing Map for Nonlinear System Identification and Control
Authors: Luzhou Liu, Jian Xiao, Long Yu
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

The self-organizing map (SOM) is an unsupervised neural network which projects high-dimensional data onto a low-dimensional. A novel model based on interval self-organizing map(ISOM) whose weights are interval numbers presented in this paper differ from conventional SOM approach. Correspondingly, a new competition algorithm based on gradient descent algorithm is proposed according to a different criterion function defined in this paper, and the convergence of the new algorithm is proved. To improve the robustness of inverse control system, the inverse controller is approximated by ISOM which is cascaded with the original to capture composite pseudo-linear system. Simulation results show that the inverse system has superior performance of tracking precision and robustness.
Design and Implementation of DLNA DMS Through IEEE1394
Authors: Gu Su Kim, Chul-Seung Kim, Hyun-Su Jang, Moon Seok Chang, Young Ik Eom
Venue: Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007 (2007)

With the technological growth of the AV(Audio and Video) equipments and the popularization of video contents, IEEE1394 for the transmission of AV data has spread fast. However, DLNA(Digital Living Network Alliance), which is a standard of the home network middleware, does not consider the transmission of AV data over IEEE1394. In this paper, we propose a scheme for transmission of AV contents over IEEE1394 in DLNA environments. In addition, by the validation test of DLNA compatibility, we show that our proposed scheme can support AV contents sharing without regard to the manufactures and transmission media.
Creation of ESTELLE/Ag Specifications Using Knowledge Bases
Authors: Henrikas Pranevicius Germanas Budnikas
Venue: Informatica (2003)

The paper presents a technique that defines creation of ESTELLE/Ag specifications using knowledge bases (KB). Application KB is created using the knowledge acquisition technique joined with a piece-linear aggregate model. The production rules of the application KB are transformed to decision tables, and the static properties of the KB are checked in PROLOGA system. Further, the application KB is combined with the defined KB of validated properties and validation method, and application KB dynamic properties are checked in the expert system in CLIPS. A validated application KB is used defining a framework of ESTELLE/Ag specification using PRAXIS editor and supplementing PRAXIS generated framework with the application functional description. The technique is illustrated with an example of a single channel queuing system.
Interaction of two-phase flow with animated models
Authors: Viorel Mihalef, Samet Kadioglu, Mark Sussman, Dimitris Metaxas, Vassilios Hurmusiadis
Venue: Graphical Models (2008)

In the present work we propose a simple and flexible fluid simulation method that enables us to perform one-way interactions of animated bodies with a coupled gas-liquid flow. This way we can animate flows in which not only the liquid but also the air is a performer. Our method allows the use of rigidly moving, articulated or deforming meshes. The paper shows how to do this practically, using a coupled level set and volume-of-fluid method. We also introduce to computer graphics a novel boundary condition, useful for open-field simulations. Animations of a swimmer in a pool, a hand scooping out water and a heart beating and spurting out either liquid or gas, showcase the strengths of our method.
Identity Based Multisignatures
Authors: Raju Gangishetti, M. Choudary Gorantla, Manik Lal Das, Ashutosh Saxena
Venue: Informatica (2006)

This paper presents identity based serial and parallel multisignature schemes using bilinear pairings. Our serial multisignature scheme requires a forced verification at every level to avoid the overlooking of the predecessors' signatures. However, in parallel multisignature scheme the verification of individual signatures is performed by a designated clerk. We show that our schemes are secure against existential forgery under adaptive chosen message attack in the random oracle model.
Pre-processing of fingerprints to improve the positioning accuracy of 802.11-based positioning systems
Authors: Hendrik Lemelson, Thomas King, Wolfgang Effelsberg
Venue: Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments (2008)

Since the first days of location-based services, the reliable estimation of a user's position has been seen as one of the key prerequisites for their success. While satellite-based systems can deliver suitable results when the user is outdoors, another solution is needed in case that he is located inside a building. Here, the position estimation with the help of 802.11 and fingerprinting algorithms promises to fill the gap. One major drawback though is the high initial effort that is needed to deploy such a fingerprinting-based 802.11 positioning system. Therefore, in this paper, novel algorithms that pre-process the data collected for the fingerprints are presented. By this pre-processing step, the amount of data that needs to be collected and therefore also the amount of time that needs to be spent collecting the data can be reduced by about 80%. Additionally, despite the reduced amount of data, the positioning accuracy cannot only be retained but even slightly improved by about 15% depending on the system's setup.
SEAC: review of three years of operation
Authors: P. D. Shupe,  Jr., R. A. Kirsch
Venue: Papers and discussions presented at the Dec. 8-10, 1953, eastern joint AIEE-IRE computer conference: information processing systems---reliability and requirements (1953)

Since September of 1950, the National Bureau of Standards has had SEAC, a digital-automatic computer, in almost continuous daily usage. It was originally conceived as an interim-computing facility for the use of the government until a more complete computing system could replace it. Consequently, in constructing the machine, it was intended to put into productive operation as soon as possible a minimal machine that could produce computed results. However, the machine proved quite reliable, and the experiments involved in its design were sufficiently successful that SEAC was expanded and kept in operation as a permanent tool at the National Bureau of Standards. It is the purpose of this paper to present some of the operating experience that has been obtained from the use of this computer and to indicate the ways in which component reliability and maintenance procedures have affected the amount of useful computation that has been obtained from SEAC.
Computationally-efficient winner determination for mixed multi-unit combinatorial auctions
Authors: Andrea Giovannucci, Meritxell Vinyals, J. A. Rodriguez-Aguilar, Jesus Cerquides
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2 (2008)

Mixed Multi-Unit Combinatorial Auctions offer a high potential to be employed for the automated assembly of supply chains of agents offering goods and services. Their winner determination problem is an NP-hard problem that can be mapped into an integer program. Nonetheless, the computational cost of the current solution hinders the application of mixed multi-unit combinatorial auctions to realistic scenarios. In this paper we propose a new integer program for mixed multi-unit combinatorial auctions that severely simplifies the problem by taking advantage of the topological characteristics of the winner determination problem. Furthermore, we provide empirical evidence showing that the new IP allows to cope with much larger supply chain formation scenarios.
YouTube3D: Accessing Web Video Streams through a 3D Interface
Authors: Fabio Pittarello, Alberto Narda
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

YouTube3D is a 3D prototype for accessing video streams on the web, conceived for stimulating exploration and information re-finding, promoting collaboration and enhancing the sense of community. It is based on a 3D metaphorical city built by the collaborative activity of different categories of users, from high-level designers that are responsible for the public areas of the world to ordinary users that populate their private areas according to their specific interests.