ppxscal/embedding_network huggingface dataset:
Optimal Hardness Results for Maximizing Agreements with Monomials
Authors: Vitaly Feldman
Venue: Proceedings of the 21st Annual IEEE Conference on Computational Complexity (2006)

We consider the problem of finding a monomial (or a term) that maximizes the agreement rate with a given set of examples over the Boolean hypercube. The problem is motivated by learning of monomials in the agnostic framework of Haussler [12] and Kearns et al. [17]. Finding a monomial with the highest agreement rate was proved to be NP-hard by Kearns and Li [15].
Rialto to B: an exercise in formal development of a language for multiple models of computation
Authors: Dag Björklund, Johan Lilius
Venue: Fundamenta Informaticae (2005)

The B method is one of the few formal methods with commercially available tool support. It has been succesfully applied in the development of several industrial applications. In this paper we present an application of the B-Method to a new domain, namely language development. We have developed an approach for translating a language with a structural operational semantics into B specifications. The language semantics is specified in separate B machines, that act as an interpreter for programs in the language. The programs, represented as abstract syntax trees, can then automatically be translated into B specifications. We have used the approach in the context of Rialto, a language for multiple models of computation. We show how Rialto programs are translated into B machines, and how the different scheduling policies that are used to interpret concurrency can be also be represented as B machines. We also discuss some shortcomings of the approach and the B-Tools that we have available.
Testing Path Generation Algorithm with Network Performance Constraints for Nondeterministic Parallel Programs
Authors: Wei Wang, Wu Yang, Lejun Zhang, Lin Guo
Venue: Proceedings of the Seventh International Conference on Web-Age Information Management Workshops (2006)

Nondeterministic behaviors of parallel programs require dedication software testing functionality. It is very difficult to test nondeterministic parallel programs systematically. Although plain reachability testing method can deal with the non-determinism, it may generate huge number of execution paths during the testing procedure. This condition is intractable to cope with in practice. Adding some appropriate constraints to plain reachability testing strategy can improve its efficiency. By analyzing the relationship between message passing behavior and the network performance, the present study proposes a limited reachability testing algorithm for message-passing parallel programs by considering network performance constraints. The number of execution paths is reduced greatly by only considering those execution paths with higher happening possibility according to the network performance constraints. In this way, large-scale parallel programs can be tested more efficiently, and the testing completeness is reasonable.
Analyzing the degree of conflict among belief functions
Authors: Weiru Liu
Venue: Artificial Intelligence (2006)

The study of alternative combination rules in DS theory when evidence is in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. These studies have mainly focused on investigating which alternative would be appropriate for which conflicting situation, under the assumption that a conflict is identified. The issue of detection (or identification) of conflict among evidence has been ignored. In this paper, we formally define when two basic belief assignments are in conflict. This definition deploys quantitative measures of both the mass of the combined belief assigned to the emptyset before normalization and the distance between betting commitments of beliefs. We argue that only when both measures are high, it is safe to say the evidence is in conflict. This definition can be served as a prerequisite for selecting appropriate combination rules.
Applying Ensembles of Multilinear Classifiers in the Frequency Domain
Authors: Christian Bauckhage, Thomas Kaster, John K. Tsotsos
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

Ensemble methods such as bootstrap, bagging or boosting have had a considerable impact on recent developments in machine learning, pattern recognition and computer vision. Theoretical and practical results alike have established that, in terms of accuracy, ensembles of weak classifiers generally outperform monolithic solutions. However, this comes at the cost of an extensive training process. The work presented in this paper results from projects on advanced human machine interaction. In scenarios like ours, online learning is a major requirement, and lengthy training is prohibitive. We therefore propose a different approach to ensemble learning. Instead of a set of weak classifiers, we combine strong, separable, multilinear discriminant functions. These are especially suited for computer vision: they train very quickly and allow for rapid classification of image content. Training different classifiers for different contexts or on semantically organized data provides ensembles of experts. We collapse a set of experts into a single multilinear function and thus achieve the same runtime for arbitrarily many classifiers as for a single one. Moreover, carrying out the classification in the frequency domain results in faster framerates. Experiments with image sequences recorded in typical home environments show that our ensemble training schemes yield high accuracy on unconstrained and cluttered data.
Mapping Policies into Autonomic Management Actions
Authors: Raphael M. Bahati, Michael A. Bauer, Elvis M. Vieira
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

Autonomic management strives to ensure that systems and applications operate as expected. Policies can be used to express required or desired behavior of systems and applications and so can be used to specify to an autonomic management system the expected operational characteristics of these systems. Such policies can be captured and mapped into autonomic management actions, providing the kinds of directives on which an autonomic management system can rely in order to meet requirements. In this paper, we look at how such techniques can be applied to manage the Apache web server in the context of self-configuration, selftuning, and overall optimization of resource use. Specifically, we look at how policies are defined and how they are realized as actions driving autonomic management.
COSMOS: a VR-based proof-of-concept interface for advanced space robot control
Authors: Jean-François Lapointe
Venue: Proceedings of the 2005 international conference on Augmented tele-existence (2005)

Virtual reality (VR) technology enables new forms of control for robot operations. This paper describes a VR-based proof-of-concept user interface that has been developed to demonstrate new control techniques for the Space Station Remote Manipulator System. Those techniques aim at improving overall operation performance and safety by using the combined power of VR, predictive displays and direct manipulation.
Similarity in Perception: A Window to Brain Organization
Authors: Zach Solan, Eytan Ruppin
Venue: Journal of Cognitive Neuroscience (2001)

This paper presents a neural model of similarity perception in identification tasks. It is based on self-organizing maps and population coding and is examined through five different identification experiments. Simulating an identification task, the neural model generates a confusion matrix that can be compared directly with that of human subjects. The model achieves a fairly accurate match with the pertaining experimental data both during training and thereafter. To achieve this fit, we find that the entire activity in the network should decline while learning the identification task, and that the population encoding of the specific stimuli should become sparse as the network organizes. Our results, thus, suggest that a self-organizing neural model employing population coding can account for identification processing while suggesting computational constraints on the underlying cortical networks.
A Novel Method for Detecting Outlying Subspaces in High-dimensional Databases Using Genetic Algorithm
Authors: Ji Zhang, Qigang Gao, Hai Wang
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Detecting outlying subspaces is a relatively new research problem in outlier-ness analysis for high-dimensional data. An outlying subspace for a given data point p is the subspace in which p is an outlier. Outlying subspace detection can facilitate a better characterization process for the detected outliers. It can also enable outlier mining for highdimensional data to be performed more accurately and efficiently. In this paper, we proposed a new method using genetic algorithm paradigm for searching outlying subspaces efficiently. We developed a technique for efficiently computing the lower and upper bounds of the distance between a given point and its kth nearest neighbor in each possible subspace. These bounds are used to speed up the fitness evaluation of the designed genetic algorithm for outlying subspace detection. We also proposed a random sampling technique to further reduce the computation of the genetic algorithm. The optimal number of sampling data is specified to ensure the accuracy of the result. We show that the proposed method is efficient and effective in handling outlying subspace detection problem by a set of experiments conducted on both synthetic and real-life datasets.
Energy Aware Topology Management in Ad Hoc Wireless Networks
Authors: T. Shiv Prakash, G. S. Badrinath, K. R. Venugopal, L. M. Patnaik
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

Topology control for ad hoc networks is needed to conserve energy and increase the network life time. In this paper we propose a Residual Energy Adaptive Re-Routing(REAR) scheme in conjunction with a Mixed Integer Linear Programming (MILP) model for prolonging the lifetime of the network. The approach is based on the multi-commodity flow which involves routing several requests from the sources to the sinks in a given network by splitting and re-routing the non-optimal flows over multiple paths. The REAR algorithm ensures uniform consumption of energy across all the nodes in the network thereby increasing the lifetime of the network. This algorithm is compared with earlier works and results observed show that the MILP algorithm in conjunction with the REAR algorithm perform better than the existing algorithms.
Single-dose Levodopa Administration and Aging Independently Disrupt Time Production
Authors: Brian C. Rakitin, Nikolaos Scarmeas, Tina Li, Chariklia Malapani, Yaakov Stern
Venue: Journal of Cognitive Neuroscience (2006)

We tested the hypothesis that age-related time production deficits are dopamine-mediated. The experiment was conducted double-blind, and with random assignment of 32 healthy aged and 32 healthy young participants to either inert placebo or levodopa (200 mg) groups. The procedure included training participants to produce two target time intervals (6 and 17 sec) in separate blocks, drug/placebo administration, a 1-hr delay, and then delayed free-recall time production retesting without feedback. Participants also performed a speeded choice reaction time (RT) task, as a control for potential dopaminergic and aging effects on attention and psychomotor speed. Results indicate that during retesting, aged participants show duration-dependent timing errors that are larger than those shown by the young participants. Levodopa administration yielded lengthened time production of both target intervals. The aging and levodopa effects did not interact. Also, aging slowed RT and increased RT variability, but levodopa had no effect on the RT. These results suggest that at this dosage and under these specific conditions, timing is dopamine-mediated but the effect of aging on time production is not. Moreover, the levodopa timing effect cannot be attributed to the effects of dopaminergic function on psychomotor speed.
Application of cyclostationary and time-frequency signal analysis to car engine diagnosis
Authors: D. Konig, J. F. Bohme
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

In modern car engines the angle of ignition has to be controlled adaptively to achieve high efficiency of the engine. This control process is usually based on evaluation of cylinder pressure or structural vibration signals. Due to the nature of the combustion process these signals are highly nonstationary. Therefore signal processing methods well suited to this special kind of signal has to be used. Based on real data experiments we show that a cyclostationary model is appropriate for constant rotation speed of the engine. Use of this model enables us to get a consistent estimate of the Wigner-Ville spectrum of the signals. This time-frequency representation has very good resolution and can give us information about the quality of sensor positions or about important parameters that can be used for adaptive control of the engine.
Minimal System Conditions to Implement Unreliable Failure Detectors
Authors: Antonio Fernandez, Ernesto Jimenez, Sergio Arevalo
Venue: Proceedings of the 12th Pacific Rim International Symposium on Dependable Computing (2006)

In this paper we explore the minimal system requirements to implement unreliable failure detectors. We first consider systems formed by lossy asynchronous and eventually timely links. On these systems we define two properties, the Weak Property and the Strong Property, depending on whether all correct processes can be reached with links that are not lossy asynchronous from one or from all correct processes, respectively. We present necessary conditions based on these properties. We show that there is no algorithm that implements 3S, , nor S (resp. 3P nor P) if we allow one single failure in a system that, when all processes are correct, does not satisfy the Weak (resp. Strong) Property. Then, we propose an algorithm that implements 3P if the Strong Property is satisfied, and 3S (andwith an additional assumption) if only the Weak Property is satisfied. For systems formed by synchronous and lossy asynchronous links only, we propose another algorithm that implements detector class P4 if the Strong Property is satisfied, and implements a new detector class S0 (andwith an additional assumption) if only the Weak Property is satisfied.
Towards Multimedia Contents Management System on Consumer Electronics Devices
Authors: YongSung Kim, TaeHoon Kim, TaeWoong Jung, HyeSoo Lee, SoHee Jang, ChangHwan Choi, HeeSeon Park
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

The need for the efficient handling of digital multimedia contents has increased tremendously as both home and mobile CE (Consumer Electronics) devices are equipped with large embedded storage such as hard disks or flash memories and are capable of handling enormous amounts of multimedia data. This paper presents Mint, an efficient multimedia contents management system for CE devices. It provides novel intuitive browsing and search interfaces by arranging multimedia data for various metadata. The system consists of the metadata extractors and the metadata core that are applicable to diverse hardware platforms and operating systems. Being applied to several CE devices has proved the usefulness of the system, especially for such devices as the digital TVs, set-top boxes and mobile phones.
Fast data access over asymmetric channels using fair and secure bandwidth sharing
Authors: Sachin Agarwal, Moshe Laifenfeld, Ari Trachtenberg, Murat Alanyali
Venue: Proceedings of the 26th IEEE International Conference on Distributed Computing Systems (2006)

We propose a peer-to-peer architecture designed to overcome asymmetries in upload/download speeds that are typical in end-user dialup, broadband and cellular wireless Internet connections. Our approach allows users at remote locations to access information stored on their home computers at rates often exceeding their home connection's upload capacity. The key to this approach is to share file data when communications are idle using random linear coding, so that, when needed, an end-user can download a file from several sources at a higher data rate than his home computer's upload capacity. We prove that our proposed system is asymptotically fair, in that (even malicious) users are proportionally assigned idle bandwidth depending on how much bandwidth they contribute, and that there is a natural incentive to join and cooperate fairly in the system. In addition, our approach provides cryptographic security and geographic data robustness to the participating peers.
GDIA: A Scalable Grid Infrastructure for Data Intensive Applications
Authors: Wei Xiaohui, Ding Zhaohui, Gaochao Xu, Ju Jiubin, Wilfred W. Li., Osamu Tatabe
Venue: Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 01 (2006)

The applications in many scientific fields, like bioinformatics and high-energy physics etc, increasingly demand the computing infrastructures can provide more computing power and support huger amount of distributed data. GDIA, built on top of CSF4 meta-scheduler and Gfarm data grid, is a scalable grid infrastructure for data intensive applications. In this paper, we presented the architecture of GDIA and the new enhancements to CSF4 in GDIA. First, a flexible user proxy delegation mechanism was introduced to enable a job running with a full proxy. With the enhancement, the jobs can access the grid services with strict security requirement like Gfarm. Secondly, we redesigned CSF4's resource manager service to support alternative protocols other than WS GRAM. At last, we discussed the scheduling issues in grids. GDIA is able to coordinate heterogeneous clusters belonging to different VOs via centralized or decentralized model. In current, GDIA has been deployed on PRAGMA's grid test bed successfully to schedule data intensive applications.
Simulation with real world network stacks
Authors: Sam Jansen, Anthony McGregor
Venue: Proceedings of the 37th conference on Winter simulation (2005)

Network simulation is used widely in network research to test new protocols, modifications to existing protocols and new ideas. The tool used in many cases is ns-2. The nature of the ns-2 protocols means that they are often based on theoretical models that might not behave in the same way as real networks. This paper presents the Network Simulation Cradle which allows real world network stacks to be used in a wrapper that allows the stacks protocols to be used in the ns-2 network simulator. The network stacks from the open source operating systems Linux, FreeBSD and OpenBSD are included in the simulation cradle as well as a stack designed for embedded systems, lwIP. Our results show that ns-2's TCP implementations do not match observed behaviour from real machines in some respects and using the Network Simulation Cradle produces results closer to real world network stacks.
Complementary Category Learning Systems Identified Using Event-Related Functional MRI
Authors: Howard J. Aizenstein, Angus W. Macdonald, V. Andrew Stenger, Robert D. Nebes, Jeris K. Larson, Stefan Ursu, Cameron S. Carter
Venue: Journal of Cognitive Neuroscience (2000)

Event-related fMRI was used to dissociate the neural systems involved in category learning with and without awareness. Ten subjects performed a speeded response category learning task. Functional MR images were acquired during both explicit and implicit learning conditions. Behavioral data showed evidence of learning in both conditions. Functional imaging data showed different activation patterns in implicit and explicit trials. Decreased activation in extrastriate region V3 was found with implicit learning, and increased activation in V3, the medial temporal lobe, and frontal regions were found with explicit learning. These results support the theory that implicit and explicit learning utilize dissociable neural systems. Moreover, in both the implicit and explicit conditions a similar pattern of decreased activation was found in parietal regions. This commonality suggests that these dissociable systems also operate in parallel.
Television Stream Structuring with Program Guides
Authors: Jean-Philippe Poli, Jean Carrive
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

We propose in this paper an original approach to the TV stream structuring problem. The goal of our work is to automatically break the TV stream into telecasts and advertisings and to label each telecast with its genre. One can think the TV stream structuring problem can be solved by an alignment of the program guide on the stream. But our study shows that, in average, only 25% of the telecasts per day are presented in the program guide. Hence, our method consists in improving statistically these program guides in order to reduce the TV stream structuring problem to a simple alignment problem. The improvement consists in adding the missing telecasts. We present an original system that lays on the modeling of past TV schedules by a Contextual Hidden Markov Model and a regression tree. Interesting results are presented at the end of the paper.
Signature-based Filtering Techniques for Structural Joins of XML Data
Authors: Huan Huo, Guoren Wang, Chuan Yang, Rui Zhou
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Queries on XML documents typically combine selections on element contents, and, via path expressions, the structural relationships between tagged elements. Efficient support for structural joins is thus the key to efficient implementation of XML queries. With a stack to keep ancestordescendant structural relationships, stack-tree join algorithm enhances the performance of structural joins by reducing deducible unnecessary comparisons. However, stack-tree join cannot prevent "unwanted" comparisons between elements that do no participate in the join. To solve this problem, we propose a signature filter, which takes advantage of encoding schemes proposed for XML and occupies a little space. Then we present an pointer-based signature filter to skip the "unwanted" elements. In order to further improve the filtering efficiency, we finally propose an optimized pointer-based filter with the conjunction of two signatures. Performance study shows that our signaturebased filters have excellent filtering performance and significantly improve the performance of structural joins.
Computing determinants of rational functions
Authors: Yasushi Umeda, Tateaki Sasaki
Venue: ACM Communications in Computer Algebra (2006)

Computation of determinants of rational functions seems to be out of thought in computer algebra so far. We first show that representing the rational function by the sum of partial fractions is absolutely necessary in the computation. We then propose a very simple technique for efficient computation: replace every distinct denominator of the rational functions in the input matrix by the inverse of an independent variable, and recover the denominators after computing the determinant as a polynomial. Some experiments show that the technique speeds up the computation by 3 ~ 6 times for the samples tested.