ppxscal/embedding_network huggingface dataset:
Learning How to Propagate Using Random Probing
Authors: Efstathios Stamatatos, Kostas Stergiou
Venue: Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2009)

In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usually only apply a standard method, typically (generalized) arc consistency, on all constraints throughout search. Advanced solvers additionally allow for the modeler to choose among an array of propagators for certain (global) constraints. Since complex interactions exist among constraints, deciding in the modelling phase which propagation method to use on given constraints can be a hard task that ideally we would like to free the user from. In this paper we propose a simple technique towards the automation of this task. Our approach exploits information gathered from a random probing preprocessing phase to automatically decide on the propagation method to be used on each constraint. As we demonstrate, data gathered though probing allows for the solver to accurately differentiate between constraints that offer little pruning as opposed to ones that achieve many domain reductions, and also to detect constraints and variables that are amenable to certain propagation methods. Experimental results from an initial evaluation of the proposed method on binary CSPs demonstrate the benefits of our approach.
STLmax joint Mutual Information for quantifying independence in the epileptic brain
Authors: Nadia Mammone, Fabio La Foresta, Francesco C. Morabito, Mario Versaci
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

Results in literature show that the convergence of the Short-Term Maximum Lyapunov Exponent (STLmax) time series, extracted from intracranial EEG recorded from patients affected by intractable temporal lobe epilepsy, is linked to the seizure onset. When the STLmax profiles of different electrode sites converge (high entrainment) a seizure is likely to occur. In this paper Renyi's Mutual information (MI) is introduced in order to investigate the independence between pairs of electrodes involved in the epileptogenesis. A scalp EEG recording and an intracranial EEG recording, including two seizures each, were analysed. STLmax was estimated for each critical electrode and then MI between couples of STLmax profiles was measured. MI showed sudden spikes that occurred 8 to 15 min before the seizure onset. Thus seizure onset appears related to a burst in MI: this suggests that seizure development might restore the independence between STLmax of critical electrode sites.
Designing a Reliable IPTV Network
Authors: Robert Doverspike, Guangzhi Li, Kostas N. Oikonomou, K. K. Ramakrishnan, Rakesh K. Sinha, Dongmei Wang, Chris Chase
Venue: IEEE Internet Computing (2009)

Meeting IPTV's quality of service constraints (such as low latency and loss) requires designing the right combination of underlying IP-transport, restoration, and video and packet recovery methods. Carriers use link-based fast reroute (FRR) as the primary transport restoration method to achieve this goal. Although we can carefully tune the link weights in the IP routing protocol to avoid traffic overlap from FRR during single link failures, multiple failures can still cause path overlap in long-distance networks. By having FRR, IGP, and multicast protocols work in harmony and with appropriate link weight assignments, this approach can help minimize path overlap during multiple failures.
Coupling Continuous and Discrete Event System Techniques for Hybrid System Diagnosability Analysis
Authors: Mehdi Bayoudh, Louise Travé-Massuyès, Xavier Olive
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In this paper we propose a hybrid system modeling framework aimed at analyzing diagnosability. In this framework, the hybrid system is seen as the composition of an underlying discrete event and an underlying continuous systems. Diagnosability of these two underlying systems are fully analyzed and new results are provided for the underlying continuous system (called the multimode system). Based on these results, a hybrid language that contains 'natural' discrete events and discrete events capturing the continuous dynamics, is defined. On the basis of this language the diagnosability definition of hybrid systems is provided. With respect to this definition, we prove that the diagnosability of the underlying continuous or the discrete event system is only a sufficient condition. Diagnosability of hybrid systems must be decided by coupling both discrete event and continuous informations. Finally, the necessary and sufficient condition of hybrid diagnosability is given.
An adaptive multigrid scheme for Bose-Einstein condensates in a periodic potential
Authors: S. -L. Chang, H. -S. Chen, C. -S. Chien, D. J. Han
Venue: Journal of Computational and Applied Mathematics (2009)

We present a novel multigrid-continuation method for treating parameter-dependent problems. The proposed algorithm which can be flexibly implemented is a generalization of the two-grid discretization schemes [C.-S. Chien, B.-W. Jeng, A two-grid discretization scheme for semilinear elliptic eigenvalue problems, SIAM J. Sci. Comput. 27 (2006) 1287-1304]. That is, approximating points on a solution curve do not necessarily lie on the same fine grid. We apply the algorithm to compute energy levels and superfluid densities of Bose-Einstein condensates (BEC) in a periodic potential. Both positive and negative scattering lengths are considered in our numerical experiments. For positive scattering length, if the chemical potential is large enough, and the domain is properly chosen, the results show that the number of peaks of the first few energy states of the 2D BEC in a periodic potential depends on the wave number of the periodic potential. Moreover, for bright solitons the number of peaks of the ground state solutions is (1d-1)^2 and (1d)^2, where the periodic potential is expressed in terms of the sine or the cosine functions, respectively. However, these formulae do not hold if the scattering length is negative. The numerical study is extended to the two-component, 1D and 2D BEC in a periodic potential.
Semiparametric estimation of a nested random effects model for the analysis of multi-level clustered failure time data
Authors: Joanna H. Shih, Shou-En Lu
Venue: Computational Statistics Data Analysis (2009)

Multi-level clustered failure time data arise when the clustering of data occurs at more than one level. It is of interest to estimate the relative risks of covariates and clustering effect of failure times at each level. We consider a nested random effect proportional hazards model, where a subcluster-specific frailty operates multiplicatively on the conditional hazard model, and its distribution function depends on a cluster-specific random frailty. Under this model, we propose a Monte-Carlo EM-based semiparametric estimation procedure to estimate regression coefficients, nonparametric baseline cumulative hazard and the association parameters. In addition, we derive a covariance matrix of the parameter estimates. We illustrate the proposed method using clustered survival data collected from a vitamin A supplementation trial in Nepal, where it is of scientific interest to assess the clustering effect of mortality within households and within villages. We use simulations to study the performance of the proposed estimation procedure.
Ontology-driven Incremental Annotation of Educational Content for Instruction Planning
Authors: Apple W. P. Fok, Horace H. S. Ip
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

Amidst the millions of pages available on the Web, it contains an invaluable educational resources pool for planning episodes of learning approach for instructions and guided learning. The un-structured nature and the lack of suitably annotated materials make retrieving the relevant learning contents that meet different pedagogical needs a difficult and time-consuming task. In this paper, we propose a framework as well as the design of a Personalized Instruction planner (PIP) that searches and annotates potentially useful learning content. Our approach is based on an ontology-driven and incremental approach to the annotation of educational content using the multi-agents infrastructure of a Personalized Education System (PES). The PIP which is a subsystem of the PES is composed of three software agents whose roles is to search, retrieve and classify potentially useful learning objects for personalized education guided by multiple ontologies that taxonomize subject domain, instructional design or pedagogy and content.
Inferring Identity Using Accelerometers in Television Remote Controls
Authors: Keng-Hao Chang, Jeffrey Hightower, Branislav Kveton
Venue: Proceedings of the 7th International Conference on Pervasive Computing (2009)

We show that accelerometers embedded in a television remote control can be used to distinguish household members based on the unique way each person wields the remote. This personalization capability can be applied to enhance digital video recorders with show recommendations per family-member instead of per device or as an enabling technology for targeted advertising. Based on five 1-3 week data sets collected from real homes, using 372 features including key press codes, key press timing, and 3-axis acceleration parameters including dominant frequency, energy, mean, and variance, we show household member identification accuracy of 70-92% with a Max-Margin Markov Network (M3N) classifier.
Integrated resource management framework for bio-grid computing
Authors: Lizhe Wang, Wei Jie
Venue: Neural, Parallel Scientific Computations (2008)

Computing grid is a promising platform that provides plenty of resource for large scientific computing applications. To achieve the performance of applications in the grid environment, careful resource management is needed. Protein alignment analysis, a typical bio-grid computing application, is a computing intensive, data parallel application, which needs data storage resources and large computing resources. This paper proposes an integrated resource management framework for bio-grid computing. We demonstrate that this kind of applications can benefit from resource management framework.
Neighbor-specific BGP: more flexible routing policies while improving global stability
Authors: Yi Wang, Michael Schapira, Jennifer Rexford
Venue: Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems (2009)

The Border Gateway Protocol (BGP) offers network administrators considerable flexibility in controlling how traffic flows through their networks. However, the interaction between routing policies in different Autonomous Systems (ASes) can lead to protocol oscillation. The best-known sufficient conditions of BGP global routing stability impose restrictions on the kinds of local routing policies individual ASes can safely implement. In this paper, we present neighbor-specific BGP (NS-BGP), a modest extension to BGP that enables a much wider range of local policies without compromising global stability. Whereas a conventional BGP-speaking router selects a single "best" route (for each destination prefix), NS-BGP allows a router to customize the route selection on behalf of each neighbor. For example, one neighbor may prefer the shortest route, another the most secure route, and yet another the least expensive route. Surprisingly, we prove that the much more flexible NS-BGP is guaranteed to be stable under much less restrictive conditions on how routers "rank" the candidate routes. We also show that it is safe to deploy NS-BGP incrementally, as a routing system with a partial deployment of NS-BGP is guaranteed to be stable, even in the presence of failure and other topology changes. In addition to our theoretical results, we also describe how NS-BGP can be deployed by individual ASes independently without changes to the BGP message format or collaboration from neighboring ASes.
Caching schemes for DCOP search algorithms
Authors: William Yeoh, Pradeep Varakantham, Sven Koenig
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Distributed Constraint Optimization (DCOP) is useful for solving agent-coordination problems. Any-space DCOP search algorithms require only a small amount of memory but can be sped up by caching information. However, their current caching schemes do not exploit the cached information when deciding which information to preempt from the cache when a new piece of information needs to be cached. Our contributions are three-fold: (1) We frame the problem as an optimization problem. (2) We introduce three new caching schemes (MaxPriority, MaxEffort and MaxUtility) that exploit the cached information in a DCOP-specific way. (3) We evaluate how the resulting speed up depends on the search strategy of the DCOP search algorithm. Our experimental results show that, on all tested DCOP problem classes, our MaxEffort and MaxUtility schemes speed up ADOPT (which uses best-first search) more than the other tested caching schemes, while our MaxPriority scheme speeds up BnB-ADOPT (which uses depth-first branch-and-bound search) at least as much as the other tested caching schemes.
Introduction to Digital Speech Processing
Authors: Lawrence R. Rabiner, Ronald W. Schafer
Venue: Foundations And Trends(R) In Signal Processing (2007)

Introduction to Digital Speech Processing provides the reader with a practical introduction to the wide range of important concepts that comprise the field of digital speech processing. It serves as an invaluable reference for students embarking on speech research as well as the experienced researcher already working in the field, who can utilize the book as a reference guide.
Strategic Foresighted Learning in Competitive Multi-Agent Games
Authors: P. J. 't Hoen, S. M. Bohte, J. A. La Poutré
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive agents an agent's actions will (likely) result in changes in the opponents policies. In addition to accounting for the estimated policies of the opponents, our algorithm also adjusts these future opponent policies by incorporating estimates of how the opponents change their policy as a reaction to ones own actions. We present results showing that agents that learn with this algorithm can successfully achieve high reward in competitive multi-agent games where myopic self-interested behavior conflicts with the long term individual interests of the players. We show that this approach successfully scales for multi-agent games of various sizes, in particular to the social dilemma type problems: from the small iterated Prisoner's Dilemma, to larger settings akin to Harding's Tragedy of the Commons. Thus, our multi-agent reinforcement algorithm is foresighted enough to correctly anticipate future rewards in the important problem class of social dilemmas, without having to resort to negotiation-like protocols or precoded strategies.
Fast interconnect and gate timing analysis for performance optimization
Authors: Soroush Abbaspour, Massoud Pedram, Amir Ajami, Chandramouli Kashyap
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2006)

Static timing analysis is a key step in the physical design optimization of VLSI designs. The lumped capacitance model for gate delay and the Elmore model for wire delay have been shown to be inadequate for wire-dominated designs. Using the effective capacitance model for the gate delay calculation and model-order reduction techniques for wire delay calculation is prohibitively expensive. In this paper, we present sufficiently accurate and highly efficient filtering algorithms for interconnect timing as well as gate timing analysis. The key idea is to partition the circuit into low and high complexity Circuits, whereby low complexity circuits are handled with efficient algorithms such as total capacitance algorithm for gate delay and the Elmore metric for wire delay and high complexity circuits are handled with sign-off algorithms. Experimental results on microprocessor designs show accuracies that are quite comparable with sign-off delay calculators with more than of 65% reduction in the computation times.
Finding optimal parameters for edit distance based sequence classification is NP-hard
Authors: Vlado Kešelj, Haibin Liu, Norbert Zeh, Christian Blouin, Chris Whidden
Venue: Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics (2009)

Parametric edit distance based classification has been applied to two significant problems in the bioinformatics area: biological sequence analysis (DNA, RNA, protein), and semantic relationship extraction from biomedical scientific literature. This method is based on the edit distance measure on sequences, with parametric costs for matching, mismatching, inserts, and deletes of letters. We present a proof that finding optimal parameter values for such classification based on training data is an NP-hard problem, which is an important claim to justify the use of heuristic methods for determining the best parameter values.
Exploiting Semantics in Collaborative Software Development Tasks
Authors: Dimitris Panagiotou, Gregoris Mentzas
Venue: Proceeding of the 2008 conference on Knowledge-Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering (2008)

Modern software development is highly knowledge intensive; it requires that software developers create and share new knowledge during their daily work. However, current software development environments are “syntantic”, i.e. they do not facilitate understanding the semantics of software artifacts and hence cannot fully support the knowledge-driven activities of developers. In this paper we present SoWiSE, a Semantic Wiki environment which focuses on the software development domain and strives to address these problems. SoWiSE aims at providing software developers such a tool to ease their daily work and facilitate cooperation, context-aware navigation, ontology-based browsing and searching, concept-based source code documentation and related problem solving.
Ranking-based clustering of heterogeneous information networks with star network schema
Authors: Yizhou Sun, Yintao Yu, Jiawei Han
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden structures of the network and the individual role played by every object in each cluster. However, although clustering on homogeneous networks has been studied over decades, clustering on heterogeneous networks has not been addressed until recently. A recent study proposed a new algorithm, RankClus, for clustering on bi-typed heterogeneous networks. However, a real-world network may consist of more than two types, and the interactions among multi-typed objects play a key role at disclosing the rich semantics that a network carries. In this paper, we study clustering of multi-typed heterogeneous networks with a star network schema and propose a novel algorithm, NetClus, that utilizes links across multityped objects to generate high-quality net-clusters. An iterative enhancement method is developed that leads to effective ranking-based clustering in such heterogeneous networks. Our experiments on DBLP data show that NetClus generates more accurate clustering results than the baseline topic model algorithm PLSA and the recently proposed algorithm, RankClus. Further, NetClus generates informative clusters, presenting good ranking and cluster membership information for each attribute object in each net-cluster.
Making Augmented Reality Practical on Mobile Phones, Part 1
Authors: Daniel Wagner, Dieter Schmalstieg
Venue: IEEE Computer Graphics and Applications (2009)

Since 2003, the authors have been developing three generations of a software framework for handheld augmented reality (AR), targeting mobile phones. This article is the first part of a discussion on the experiences and design decisions that resulted in the current software framework, Studierstube ES (Embedded System). The authors describe the restrictions of the mobile phone platform and a software architecture that allows fast development of mobile phone AR applications.
Reward shaping for valuing communications during multi-agent coordination
Authors: Simon A. Williamson, Enrico H. Gerding, Nicholas R. Jennings
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

Decentralised coordination in multi-agent systems is typically achieved using communication. However, in many cases, communication is expensive to utilise because there is limited bandwidth, it may be dangerous to communicate, or communication may simply be unavailable at times. In this context, we argue for a rational approach to communication --- if it has a cost, the agents should be able to calculate a value of communicating. By doing this, the agents can balance the need to communicate with the cost of doing so. In this research, we present a novel model of rational communication, that uses reward shaping to value communications, and employ this valuation in decentralised POMDP policy generation. In this context, reward shaping is the process by which expectations over joint actions are adjusted based on how coordinated the agent team is. An empirical evaluation of the benefits of this approach is presented in two domains. First, in the context of an idealised bench-mark problem, the multiagent Tiger problem, our method is shown to require significantly less communication (up to 30% fewer messages) and still achieves a 30% performance improvement over the current state of the art. Second, in the context of a larger-scale problem, RoboCupRescue, our method is shown to scale well, and operate without recourse to significant amounts of domain knowledge.
Techniques for software quality analysis of binaries: applied to Windows and Linux
Authors: Thomas Panas, Daniel Quinlan
Venue: Proceedings of the 2nd International Workshop on Defects in Large Software Systems: Held in conjunction with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2009) (2009)

In this paper we present our efforts to measure different quality aspects of large-scale, binary software. We apply four well established metrics to binary versions of Windows and Debian Linux, analyze our results and discuss our observations. It is surprising to see that our metrics, which search for well known bad coding habits, result with so many violations. It appears that although bad and insecure software development practices are well understood and documented, in practice, recommended coding styles are not followed. Our work evaluates binary versions of software, allowing us to inspect software quality without the need of source code. We believe that this approach, if successful, could lead in the future to better priced software. This is because the quality of software bought today is not transparent to its users.