ppxscal/embedding_network huggingface dataset:
Sparsity and model selection through convex penalties: structured selection, covariance selection and some theory
Authors: Bin Yu
Venue:  (2008)

High-dimensional data sets requires model selection methods capable of controlling model complexity and goodness of fit to the observed data. Such problems constitute a natural setting where to apply penalized empirical risk minimization. Ideally, a model should be interpretable and easy to compute. Sparsity in a parameter space is a proxy for interpretability and is traditionally enforced in statistics by penalizing the dimensionality of the parameter space. Such penalties lead to interpretable models but involve a combinatorial search and are thus computationally costly to obtain, obtained by penalizing the &ell; 1-norm of the fitted parameters. In the first article of this thesis, we present a simulation based comparison of two traditional approaches to tackle the computational burden of dimensionality based penalties: the more traditional greedy algorithms and the more recent convex relaxation methods. We conclude that convex relaxation yields estimates that are better in terms of predictive performance and comparable in terms of parameter selection provided the appropriate criterion is used for each application. Then, we introduce the family of Composite Absolute Penalties (CAP). Penalty functions in this family are capable of performing grouped and hierarchical selection. Building upon convexity of CAP penalties, algorithms for efficiently computing the CAP estimates for different levels of penalization and methods for choosing an appropriate level of penalization are proposed. The predictive and parsimony gains of employing CAP penalties are shown by means of a series of simulated examples. Next, we introduce the Sparse Pseudo-Likelihood Inverse Covariance Estimator (SPLICE): a &ell;1-penalized pseudo-likelihood estimate of precision matrices. SPLICE estimates can be efficiently computed at the higher range of values of the regularization parameter where our heuristic analysis suggests that the pseudo-likelihood approximation works best. Simulation studies suggest that, with scarce data, many selection criteria chose higher regularization levels where the performance of the exact and pseudo-likelihood estimates is comparable. Finally, we extend previous results in the literature so they can be used to characterize asymptotic distribution of many alternative combination of loss and penalty functions for parametric (low-dimensional) models. The approximations used to derive such asymptotic results also leads to a simple criterion determining sufficient conditions for the existence of a regularization level at which the signs of the penalized parameter estimate agree with the signs of the "true parameter".
The dynamics of strategic behavior in retail banking markets: the cases of the united states and china
Authors: Darren Filson
Venue:  (2008)

The goal of my dissertation is to uncover the dynamics of competitive strategies and performance in retail banking markets. I focus on the U.S. and Chinese banking markets because both have experienced structural changes that warrant a dynamic analysis. The banking industry in the U.S. has experienced a series of deregulations and large amounts of entry, exit, and mergers accompanied by the rapid diffusion of the Internet and other technological changes. In contrast, most of the banks in China are almost entirely government-owned and the four largest state-owned commercial banks possess market power and account for over half of total industry assets. The central government has implemented a series of reforms intended to commercialize the banks and to prepare the banks for foreign competition after the WTO accession. I develop a stationary infinite-horizon computational dynamic equilibrium duopoly model of value-maximizing banks that focuses on individual retail banking markets. The resulting model uncovers the dynamics of growth and competitive behavior of small and large banks in a local market. Improving upon existing theoretical models of competition in retail banking, this model links price and non-price competition strategies that banks adopt. The results suggest that the newer and smaller banks usually offer a higher deposit interest rate than the established and larger banks. In contrast, the larger banks are more likely to engage in non-price competition. Hypotheses suggested by the computational model are supported by the empirical studies in the literature. However, statistics on 26 single-market banks in 13 U.S. retail banking markets and a case study in Chapter Two show only weak and statistically insignificant evidence. Theoretical and empirical analysis on China's commercial banks' lending behavior in Chapter Three focuses on the post-1994 period when a series of reforms intended to commercialize the banks took place. The absence of more clear-cut, consistent evidence may suggest that little has actually changed in the big four's practice.
Internet-scale service infrastructure efficiency
Authors: James Hamilton
Venue: ACM SIGARCH Computer Architecture News (2009)

High-scale cloud services provide economies of scale of five to ten over small-scale deployments, and are becoming a large part of both enterprise information processing and consumer services. Even very large enterprise IT deployments have quite different cost drivers and optimizations points from internet-scale services. The former are people-dominated from a cost perspective whereas internet-scale service costs are driven by server hardware and infrastructure with people costs fading into the noise at less than 10%. In this talk we inventory where the infrastructure costs are in internet-scale services. We track power distribution from 115KV at the property line through all conversions into the data center tracking the losses to final delivery at semiconductor voltage levels. We track cooling and all the energy conversions from power dissipation through release to the environment outside of the building. Understanding where the costs and inefficiencies lie, we'll look more closely at cooling and overall mechanical system design, server hardware design, and software techniques including graceful degradation mode, power yield management, and resource consumption shaping.
Proactive key management protocol for multicast services
Authors: Dong-Hyun Je, Seung-Woo Seo
Venue: Proceedings of the 4th International Conference on Future Internet Technologies (2009)

A group key management is essential scheme guaranteeing data confidentiality in multicast. To provide the strict secrecy in group communication, the rekeying delay has to be minimized. In this paper, we propose a new group key management protocol, called 'Proactive Key Management (PKM)'. We classify the key updating processes into 5 processes in operation order of key updating. By performing 2 key updating process before next rekeying start, PKM can remarkably reduce the rekeying delay. Specifically, we show through simulation result that by applying PKM, the rekeying delay can be reduced up to 80%.
Cognitive Primitives for Automated Learning
Authors: Sudharsan Iyengar
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

Artificial Intelligence deals with the automated simulation of human intelligent behavior. Various aspects of human faculties are tackled using computational models. It is clear that brain as a cognitive machine is significantly different from a computer. A general intelligent machine needs to incorporate primitives that are identical or similar to those intrinsic to human. We argue for the identification, verification, and development of technologies that will deliver core primitives that are fundamental to human cognition that are applicable to various domains. Mnemonics for aural and for visual cognition are presented in [2, 3]. We propose a generalized set of cognitive primitives that can specialized to various applications viz. a) Existential, b) Structured Recurrence, c) Relative Attachment, d) Harmonized Counterparts, e) Cordial Counterparts and f) Discriminate Counterparts.
Research on Segment Acoustic Model Based Mandarin LVCSR
Authors: Wenju Liu, Yun Tang, Shouye Peng
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

SM has shown a better performance than HMM in connected word recognition system; however, no reports we have read show that SM has been applied in LVCSR as decoding acoustic model because of the restriction of its complexity. We have preliminarily built a SM based mandarin LVCSR system which adopts CART and global tying to tie the parameters in the triphone models and the fast SM algorithm, CF algorithm and two-level pruning to enhance the speed of decoding. The system achieves 87.09% syllable accuracy in Test-863 data corpus within 4 real times. We believe SM offers an alternative choice for LVCSR system though further research for its fast algorithms by rational utilization of its structure information.
CHALLENGE FRAP --A Combination Guide and Reporting Tool for Problem-based Exercises
Authors: Terry M. Stewart, William R. MacIntyre, Victor J. Galea
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)

A freeware editing tool, CHALLENGE FRAP, has been developed for use as both a guide and a reporting device for students undertaking an investigative, problem-solving task. This paper describes the tool, and presents two case studies from different subject domains, showing its use.
A Novel Weight-Based Immune Genetic Algorithm for Multiobjective Optimization Problems
Authors: Guixia He, Jiaquan Gao
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The weight-based multiobjective evolutionary algorithms have been criticized mainly for the following aspects: (1) difficulty in finding Pareto-optimal solutions in problems having nonconvex Pareto-optimal region, and (2) non-elitism approach for most cases, and (3) difficulty in generating uniformly distributed Pareto-optimal solutions. In this paper, we propose a weight-based multiobjective immune genetic algorithm(MOIGA), which alleviates all the above three difficulties. In this proposed algorithm, a randomly weighted sum of multiple objectives is used as a fitness function. An immune operator is adopted to increase the diversity of the population. Specifically, a new mate selection approach called tournament selection algorithm with similar individuals (TSASI) and a new environmental selection approach named truncation algorithm with similar individuals (TASI) are presented. Simulation results show MOIGA outperforms NSGA-II and RWGA.
Freeway exit ramp traffic flow research based on computer simulation
Authors: Jian John Lu
Venue:  (2008)

Interstate highways are one of the most important components of the transportation infrastructure in America. Freeway ramps play an important role in the whole interstate transportation system. This paper researches the traffic flow characteristics of four typical exit ramps in USA, which are tapered one-lane exit, tapered two-lane exit, parallel one-lane exit and parallel two-lane exit. Computer simulation software, such as CORSIM and HCS are applied as the main tools in this research. ANOVA and Tukey are used for statistical purpose. It compares the maximum capacity, average running speed and the total lane change number of those four exit ramps. It is found that no matter in terms of traffic discharging rate or total lane charging number; the tapered two-lane exit has the best operational performance. Tapered one-lane exit ramp has the least capacity. Parallel one-lane exit and parallel two-lane exit have very limited traffic operational difference in terms of capacity and running speed. It is recommended that parallel two-lane exit ramp should not be designed along the freeway if the right of way along arterial road is enough. It is observed from the simulation data that the grade of freeway, truck percentage, restricted to the truck use of certain lane(s) and the location of exit sign have significant impact on the running speed and total lane change number. An uphill can decrease the running speed dramatically while more truck brings more lane change, causing safety concerns. It is found that when trucks are restricted to the right two most lane, there will be less lane change number comparing with trucks are not restricted. Location of exit sign operates well at the distance between 4000 ft to 5000 ft. does have a significant impact on the operational speed and total lane change number before, within or after functional area of an exit, based on the data analysis of simulation runs.
A self-healing key distribution scheme based on vector space secret sharing and one way hash chains
Authors: Biming Tian, Song Han, Tharam S. Dillon, Sajal Das
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

An efficient self-healing key distribution scheme with revocation capability is proposed for secure group communication in wireless networks. The scheme bases on vector space secret sharing and one way hash function techniques. Vector space secret sharing helps to realize general monotone decreasing structures for the family of subsets of users that can be revoked instead of a threshold one. One way hash chains contribute to reduce communication overhead. Furthermore, the most prominent characteristic of our scheme is resisting collusion between the new joined users and the revoked users, which is fatal weakness of hash function based self-healing key distribution schemes.
Feature Selection in a Low Cost Signature Recognition System Based on Normalized Signatures and Fractional Distances
Authors: C. Vivaracho-Pascual, J. Pascual-Gaspar, V. Cardeñoso-Payo
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

In a previous work a new proposal for an efficient on-line signature recognition system with very low computational load and storage requirements was presented. This proposal is based on the use of size normalized signatures, which allows for similarity estimation, usually based on DTW or HMMs, to be performed by an easy distance calcultaion between vectors, which is computed using fractional distance. Here, a method to select representative features from the normalized signatures is presented. Only the most stable features in the training set are used for distance estimation. This supposes a larger reduction in system requirements, while the system performance is increased. The verification task has been carried out. The results achieved are about 30% and 20% better with skilled and random forgeries, respectively, than those achieved with a DTW-based system, with storage requirements between 15 and 142 times lesser and a processing speed between 274 and 926 times greater. The security of the system is also enhanced as only the representative features need to be stored, it being impossible to recover the original signature from these.
An RDF-based distributed expert system
Authors: Napat Prapakorn, Suphamit Chittayasothorn
Venue: WSEAS Transactions on Computers (2009)

An expert system or knowledge-based system comprises of a knowledge base and an inference engine in which their expertise knowledge is represented. The knowledge can be called upon when needed to solve a problem by the inference engine. In a large expert system, the knowledge base can be represented using frames. Hence they are called frame-based expert system or frame-based system. To avoid too many communication traffics during inferences, a distributed expert system, an expert system with an inference engine on its external knowledge base side is presented. It is an expert system which has an RDF external knowledge base for improved flexibility and mobility in knowledge sharing. This research presents a design and implementation of a Frame-based RDF expert system which has a RDF/XML database as its external knowledge base. The external knowledge base uses frame as its knowledge representation stored in RDF/XML format so that it can be placed on the WWW (World Wide Web) which is, ideally, accessible from anywhere. With this capability, an expert system will be enriched with flexibility and mobility in knowledge sharing.
Application of evolutionary algorithm on aerodynamic wing optimisation
Authors: Miroslav Červenka, Ivan Zelinka
Venue: Proceedings of the 2nd conference on European computing conference (2008)

Search for safety and high efficiency is the driving force in the aerospace industry. This paper reports on application of a relatively new and very promising evolutionary algorithm SOMA with the intent to answer the question on optimal wing geometry. We describe aerodynamic model of the wing, the evolutionary optimisation process and results we obtained. In this contribution present a modern, high performance global optimisation algorithm applied on real engineering application resulting into a set of evolutionary-designed wings which we developed in cooperation with a leading civil aircraft design bureau and manufacturer.
Lossless and Near-Lossless Image Compression Scheme Utilizing Blending-Prediction-Based Approach
Authors: Grzegorz Ulacha, Piotr Dziurzanski
Venue: Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers (2008)

An approach for lossless and near-lossless compression of still images together with its system-level multi-core hardware model utilizing blending-prediction-based technique is presented in this paper. We provide a mathematical background of the proposed approach and utilize a Network on Chip type of connection in the hardware model which benefits from a new multi-path routing algorithm and heuristic algorithms for core mapping realizing subsequent stages of the compression algorithm. The experimental results confirming the advantages of the proposed approach are provided.
Scope Dominance with Generalized Quantifiers
Authors: Gilad Ben-Avi, Yoad Winter
Venue: Languages: From Formal to Natural: Essays Dedicated to Nissim Francez on the Occasion of His 65th Birthday (2009)

When two quantifiers Q 1 and Q 2 satisfy the scheme Q 1 x Q 2 y ¿¿Q 2 y Q 1 x ¿, we say that Q 1 is scopally dominant over Q 2. This relation is central in analyzing and computing entailment relations between different readings of ambiguous sentences in natural language. This paper reviews the known results on scope dominance and mentions some open problems.
On Selecting the Best Pre-processing Method for Affymetrix Genechips
Authors: J. P. Florido, H. Pomares, I. Rojas, J. C. Calvo, J. M. Urquiza, M. Gonzalo Claros
Venue: Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence (2009)

Affymetrix High Oligonucleotide expression arrays, also known as Affymetrix GeneChips, are widely used for the high-throughput assessment of gene expression of thousands of genes simultaneously. Although disputed by several authors, there are non-biological variations and systematic biases that must be removed as much as possible before an absolute expression level for every gene is assessed. Several pre-processing methods are available in the literature and five common ones (RMA, GCRMA, MAS5, dChip and VSN) and two customized Loess methods are benchmarked in terms of data variability, similarity of data distributions and correlation coefficient among replicated slides in a variety of real examples. Besides, it will be checked how the variant and invariant genes can influence on preprocessing performance.
Classification of DNA microarray data with Random Projection Ensembles of Polynomial SVMs
Authors: Alberto Bertoni, Raffaella Folgieri, Giorgio Valentini
Venue: Proceeding of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008 (2009)

In this paper we propose and experimentally analyze ensemble methods based on random projections (as feature extraction method) and SVM with polynomial kernels (as learning algorithm). We show that, under suitable conditions, polynomial kernels are approximately preserved by random projections, with a degradation related to the square of the degree of the polynomial. Experimental results with Random Subspace and Random Projection ensembles of polynomial SVMs, support the hypothesis the low degree polynomial kernels, introducing with high probability lower distortions in the projected data, are better suited to the classification of high dimensional DNA microarray data.
SOA Approach to Integration: XML, Web services, ESB, and BPEL in real-world SOA projects
Authors: Poornachandra Sarang
Venue:  (2007)

This book shows how to define SOA integration architecture, what technologies to use, and how to best integrate existing applications with modern e-business solutions. The book also shows how to develop web services, how to process and manage XML documents from JEE and .NET platforms, and how to use ESBs and BPEL executable business processes within SOA architecture. Integration of applications within a business and between different businesses is becoming more and more important. The needs for up-to-date information that is accessible from almost everywhere and developing e-business solutions -- particularly business to business -- require that developers find solutions for integrating diverse, heterogeneous applications, developed in different architectures and programming languages and on different platforms. They have to do this quickly and cost effectively, but still preserve the architecture and deliver robust solutions that are maintainable over time. Integration is a difficult task. This book focuses on the SOA approach to integration of existing (legacy) applications and newly developed solutions, using modern technologies, particularly web services, XML, ESB, and BPEL. The book shows how to define SOA for integration, what integration patterns to use, which technologies to use, and how to best integrate existing applications with modern e-business solutions. It also shows how to develop web services and BPEL processes, and how to process and manage XML documents from the JEE and .NET platforms. Finally, it also explains how to integrate both platforms using web services and ESBs. Service-Oriented Architectures and SOA approach to integrationSOA architectural design and domain-specific modelsCommon Integration Patterns and how they can be best solved using Web services, BPEL and Enterprise Service Bus (ESB)Concepts behind SOA standards, security, transactions, and how to efficiently work with XML This book is for architects and senior developers who are responsible for setting up SOA for integration for applications within the enterprise (intra-enterprise integration) and applications across enterprises (inter-enterprise integration or B2B). The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Integrated CE tools for postponed aerospace product and process decisions
Authors: Cássio Dias Gonçalves, Luís Gonzaga Trabasso, Geilson Loureiro
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

This paper aims to develop, demonstrate and justify a quantitative method that identifies the best kind and optimal level of postponement that should be adopted in an Aerospace Company to promote production cost reduction, improving customer service, offering short times of delivery and increasing the overall program profit. This method also intends to determine the best time to make the main decisions during the product development project.