ppxscal/embedding_network huggingface dataset:
SMVLLE: An Efficient Dimension Reduction Scheme
Authors: Heyong Wang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

To overcome the problems associated with high dimensionality, such as high storage and classification time, dimension reduction is usually applied to the vectors to concentrate relevant information in a low dimension. Locally Linear Embedding (LLE) is a well-known dimension reduction scheme. However, it works with vectorized representations of images and does not take into account the spatial locality relation information of images, thus some information will be lost. In this paper, a new dimension reduction scheme, called Small Matrix Vector Locally Linear Embedding (SMVLLE), is presented. Using SMVLLE which is based on small matrix cover for dimension reduction can reduce the loss of spatial locality relation information among image pixels, because this scheme works directly with images in their native state. Experiments on handwritten digit images and texture images show that SMVLLE is superior to LLE in terms of quality of the dimension reduction.
Preserving Privacy versus Data Retention
Authors: Markus Hinkelmann, Andreas Jakoby
Venue: Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation (2009)

The retention of communication data has recently attracted much public interest, mostly because of the possibility of its misuse. In this paper, we present protocols that address the privacy concerns of the communication partners. Our data retention protocols store streams of encrypted data items, some of which may be flagged as critical (representing misbehavior). The frequent occurrence of critical data items justifies the self-decryption of all recently stored data items, critical or not. Our first protocol allows the party gathering the retained data to decrypt all data items collected within, say, the last half year whenever the number of critical data items reaches some threshold within, say, the last month. The protocol ensures that the senders of data remain anonymous but may reveal that different critical data items came from the same sender. Our second, computationally more complex scheme obscures this affiliation of critical data with high probability.
A Formal Model of Emotions: Integrating Qualitative and Quantitative Aspects
Authors: Bas R. Steunebrink, Mehdi Dastani, John-Jules Ch. Meyer
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

When constructing a formal model of emotions for intelligent agents, two types of aspects have to be taken into account. First, qualitative aspects pertain to the conditions that elicit emotions. Second, quantitative aspects pertain to the actual experience and intensity of elicited emotions. In this paper, we show how the qualitative aspects of a well-known psychological model of human emotions can be formalized in an agent specification language and how its quantitative aspects can be integrated into this model. Furthermore, we discuss several unspecified details and implicit assumptions in the psychological model that are explicated by this effort.
TCP-Cherry for satellite IP networks: Analytical model and performance evaluation
Authors: Satoshi Utsumi, Salahuddin Muhammad Salim Zabir, Norio Shiratori
Venue: Computer Communications (2009)

TCP-Cherry is a novel TCP congestion control scheme that we devised for ensuring high performance over satellite IP networks and the alikes which are characterized by long propagation delays and high link errors. In TCP-Cherry, two new algorithms, Fast-Forward Start and First-Aid Recovery, have been proposed for congestion control. Our algorithms use supplement segments, i.e., low-priority segments to probe the available bandwidth in the network for the TCP connections along with carrying new data blocks. In this paper, we present our new congestion control scheme, TCP-Cherry and devise an analytical model for it. Our major contributions in this paper include the analytical model and equations for performance evaluation, validation of the analytical model through comparison between analytical and simulation results and devising a guideline to tune the buffer related parameters both at the sender as well as the receiver ends for optimum throughput performance. Experiments show that simulation results and the calculated throughput from our analytical model match quite closely, thereby verifying the appropriateness of the model. In addition, from analysis of simulation results, we discover that a buffer size at the receiver, rwnd, that is around four times maxcwnd, or the maximum congestion window at the sender side, is likely to maintain high throughput over a wide range of operating conditions.
Interactive Generation and Modification of Cutaway Illustrations for Polygonal Models
Authors: Sebastian Knödel, Martin Hachet, Pascal Guitton
Venue: Proceedings of the 10th International Symposium on Smart Graphics (2009)

We present a system for creating appealing illustrative cutaway renderings. This system bases on simple sketch-based interfaces and stylized rendering techniques for the study of elaborate 3D models. Since interactive visualization technology found its way to the general public, there is a demand for novel interaction techniques that allow easy exploration of the displayed illustrations. Hence, our system lets users create individual cutaway views to focus on hidden objects. At the same time, important contextual information is emphasized by illustrative rendering techniques.
Game Theory and Cognitive Radio Based Wireless Networks
Authors: Saurabh Mehta, K. S. Kwak
Venue: Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications (2009)

The ability to model individual, independent decision makers whose actions potentially affect all other decision makers renders game theory particularly attractive to apply to various fields of Information technology, especially, to analyze the performance of wireless networks. In this paper, we discuss how various interactions in cognitive radio based wireless networks can be modeled as a game at different levels of protocol stack. This allows the analysis of existing protocols and resource management schemes, as well as the design of equilibrium-inducing mechanisms that provide incentives for individual users to behave in socially-constructive ways. In nutshell, this paper serves two main objectives; first, to model some of the fundamental questions on cognitive radio based wireless networks as interactive games between the nodes and second, to gain our understanding on inter-discipline research issues.
An efficient projection for l1, &infin; regularization
Authors: Ariadna Quattoni, Xavier Carreras, Michael Collins, Trevor Darrell
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

In recent years the l1, &infin; norm has been proposed for joint regularization. In essence, this type of regularization aims at extending the l1 framework for learning sparse models to a setting where the goal is to learn a set of jointly sparse models. In this paper we derive a simple and effective projected gradient method for optimization of l1, &infin; regularized problems. The main challenge in developing such a method resides on being able to compute efficient projections to the l1, &infin; ball. We present an algorithm that works in O(n log n) time and O(n) memory where n is the number of parameters. We test our algorithm in a multi-task image annotation problem. Our results show that l1, &infin; leads to better performance than both l2 and l1 regularization and that it is is effective in discovering jointly sparse solutions.
Automated explanation of financial data
Authors: H. A. M. Daniels, E. A. M. Caron
Venue: International Journal of Intelligent Systems in Accounting and Finance Management (2009)

We describe a methodology for explanation generation in financial knowledge-based systems. This offers the possibility to generate explanations and diagnostics automatically to support business decision tasks. The central goal is the identification of specific knowledge structures and reasoning methods required to construct computerized explanations from financial data and models. A multistep look-ahead algorithm is proposed that deals with so-called cancelling-out effects, which are a common phenomenon in financial data sets. Our method is an extension of the traditional variance decomposition in accounting. The method was tested on a case-study conducted for Statistics Netherlands involving the comparison of financial figures of firms in the Dutch retail branch. Copyright &copy; 2009 John Wiley & Sons, Inc.
Bulk-Insertion Sort: Towards Composite Measures of Presortedness
Authors: Riku Saikkonen, Eljas Soisalon-Soininen
Venue: Proceedings of the 8th International Symposium on Experimental Algorithms (2009)

Well-known measures of presortedness, among others, are the number of inversions needed to sort the input sequence, or the minimal number of blocks of consecutive elements that remain as such in the sorted sequence. In this paper we study the problem of possible composition of measures. For example, after determining the blocks in an input sequence, it is meaningful to measure how many inversions of the blocks are needed to finally sort the sequence. With composite measures in mind we introduce the idea of applying bulk insertions to improve adaptive binary-tree (AVL) sorting; this is done by combining local insertion sort with bulk-insertion methods. We show that bulk-insertion sort is optimally adaptive with respect to the number of bulks and with respect to the number of inversions in the original input. As to composite measures, we define a new measure that tells how many inversions are needed when the extracted bulks form the input. Bulk-insertion sort is shown to be adaptive with respect to this measure. Our experiments show that applying bulk insertion in AVL-tree sorting considerably reduces the number of comparisons and time needed to sort nearly sorted sequences.
Virtualraid: a mass storage architecture for out-of-core applications
Authors: Milos Ercegovac, Lawrence Mcnamee
Venue:  (1997)

To support the performance requirements of modern computer systems, parallel disk systems have evolved. Because disks suffer from independent failures, parallel storage systems suffer from degraded reliability as systems increase in size. This drawback is addressed by incorporating redundancy in the form of additional disks. This redundancy results in higher cost and degraded performance. To improve performance, expensive non-volatile cache memories are commonly used. Memories are required to be non-volatile to prevent unrecoverable data loss in the event of system failure, including power failure, operator error, hardware breakdown, or software crash. This dissertation proposes a new approach to parallel storage for Out-of-Core applications. Our storage solution combines (1) a redundant RAID Level for permanent storage, and (2) a striped disk array for temporary storage into a dual configuration RAID, resulting in performance superior to redundant RAIDs. Our approach also provides higher storage efficiency than redundant disk arrays, because temporary files require no redundancy. The drawback of not providing redundancy for temporary files is that rollback is required for system crashes or disk failures to re-create temporary files. Because temporary data need not be recovered, temporary metadata is not stored to disk, resulting in fewer disk accesses. To analyze the performance improvements of our proposed architectures, we created a suite of application benchmarks. These applications were traced to characterize these benchmarks. These traces were then analyzed using a simulator of our proposed architectures. Our architecture observed up to a 10X performance improvement in raw disk access times over the conventional RAID 5 case, resulting in an overall performance improvement of 1.2X for most of the benchmarks. A raw disk performance improvement of 3X was observed over a cached-RAID 5 architecture. virtualRAID benefited from not having to store temporary metadata to disk. Full simulation results are presented for virtualRAID, non-cached RAID 5, cached RAID 5, and a RAID 0 configuration. The partitioning structure can significantly degrade performance for applications that contain high concentration of seek accesses. We will present a novel reconfigurable RAID architecture that stores temporary non-redundant data along with permanent redundant data. By optimizing the partition layout, this approach improves performance by up to 2X over our original proposed architecture, and up to 3.37X over the conventional RAID 5 case. Since this architecture minimizes the number of required seeks and minimizes temporary metadata accesses, it also outperforms a non-redundant RAID 0 disk array by a factor of up to 1.7X.
A slotted ALOHA protocol with cooperative diversity
Authors: Ramiro Samano-Robles, Atilio Gameiro
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

Over the last few years, the area of cooperative communications has regained attention within the physical layer community. However, existing works on cooperative random access protocols are relatively scarce and biased towards their physical layer properties, thus leaving unattended important problems of the medium access control (MAC) sublayer such as calculation of the backlog delay, design of appropriate back-off retransmission strategies, and stability evaluation, among many others. This paper partially fills this gap by studying the general performance of a symmetrical Slotted ALOHA protocol in which a cooperative relaying phase is enabled in order to improve the decoding probability of collision-free transmissions. Infinite and finite user schemes are used, and for the latter, Bernoulli and Markov models are further employed to study the steady- and the dynamic-state properties of the protocol, respectively. A stochastic reception model is presented which fairly describes the underlying physical layer events from the perspective of the MAC sublayer, including correct packet decoding probabilities, relay node availability, and error detection capabilities. Important results regarding the boundaries for optimum performance of cooperative relaying schemes and useful guidelines for the design of optimum relaying strategies are here derived and discussed.
Agents and Service-Oriented Computing for Autonomic Computing: A Research Agenda
Authors: Frances M. T. Brazier, Jeffrey O. Kephart, H. Van Dyke Parunak, Michael N. Huhns
Venue: IEEE Internet Computing (2009)

Autonomic computing is the solution proposed to cope with the complexity of today's computing environments. Self-management, an important element of autonomic computing, is also characteristic of single and multiagent systems, as well as systems based on service-oriented architectures. Combining these technologies can be profitable for all — in particular, for the development of autonomic computing systems.
Visualization of Structured Data via Generative Probabilistic Modeling
Authors: Nikolaos Gianniotis, Peter Tiňo
Venue: Similarity-Based Clustering: Recent Developments and Biomedical Applications (2009)

We propose a generative probabilistic approach to constructing topographic maps of sequences and tree-structured data. The model formulation specifies a low-dimensional manifold of local noise models on the structured data. The manifold of noise models is induced by a smooth mapping from a low dimensional Euclidean latent space to the parameter space of local noise models. In this paper, we consider noise models endowed with hidden Markovian state space structure, namely Hidden Markov Tree Models (HMTM) and Hidden Markov Models (HMM). Compared with recursive extensions of the traditional Self-Organizing Map that can be used to visualize sequential or tree-structured data, topographic maps formulated within this framework possess a number of advantages such as a well defined cost function that drives the model optimization, the ability to test for overfitting and the accommodation of alternative local noise models implicitly expressing different notions of structured data similarity. Additionally, using information geometry one can calculate magnification factors on the constructed topographic maps. Magnification factors are a useful tool for cluster detection in non-linear topographic map formulations. We demonstrate the framework on two artificial data sets and chorals by J.S. Bach represented as sequences, as well as on images represented as trees.
Detection of object abandonment using temporal logic
Authors: Medha Bhargava, Chia-Chih Chen, M. S. Ryoo, J. K. Aggarwal
Venue: Machine Vision and Applications (2009)

This paper describes a novel framework for a smart threat detection system that uses computer vision to capture, exploit and interpret the temporal flow of events related to the abandonment of an object. Our approach uses contextual information along with an analysis of the causal progression of events to decide whether or not an alarm should be raised. When an unattended object is detected, the system traces it back in time to determine and record who its most likely owner(s) may be. Through subsequent frames, the system searches the scene for the owner and issues an alert if no match is found for the owner over a given period of time. Our algorithm has been successfully tested on two benchmark datasets (PETS 2006 Benchmark Data, 2006; i-LIDS Dataset for AVSS, 2007), and yielded results that are substantially more accurate than similar systems developed by other academic and industrial research groups.
A linguistic service ontology for language infrastructures
Authors: Yoshihiko Hayashi
Venue: Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions (2007)

This paper introduces conceptual framework of an ontology for describing linguistic services on network-based language infrastructures. The ontology defines a taxonomy of processing resources and the associated static language resources. It also develops a sub-ontology for abstract linguistic objects such as expression, meaning, and description; these help define functionalities of a linguistic service. The proposed ontology is expected to serve as a solid basis for the interoperability of technical elements in language infrastructures.
Large-scale ETD repositories: a case study of a digital library application
Authors: Adam Mikeal, James Creel, Alexey Maslov, Scott Phillips, John Leggett, Mark McFarland
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

We describe the implementation of a statewide system for managing and preserving electronic theses and dissertations (ETDs) from Texas universities. We further explain the theoretical, technical and political issues that arose during the implementation of this system. These issues range from technical components developed by TDL 'such as a customized workflow management application and adding OAI-ORE capabilities to DSpace' to human-centered issues such as stakeholder engagement and participation. Our experiences reflect the challenges, expected and unexpected, that others will face when attempting to build digital library applications to scale.
Combinatorial prediction markets for event hierarchies
Authors: Mingyu Guo, David M. Pennock
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

We study combinatorial prediction markets where agents bet on the sum of values at any tree node in a hierarchy of events, for example the sum of page views among all the children within a web sub-domain. We propose three expressive betting languages that seem natural, and analyze the complexity of pricing using Hanson's logarithmic market scoring rule (LMSR) market maker. Sum of arbitrary subset (SAS) allows agents to bet on the weighted sum of an arbitrary subset of values. Sum with varying weights (SVW) allows agents to set their own weights in their bets but restricts them to only bet on subsets that correspond to tree nodes in a fixed hierarchy. We show that LMSR pricing is NP-hard for both SAS and SVW. Sum with predefined weights (SPW) also restricts bets to nodes in a hierarchy, but using predefined weights. We derive a polynomial time pricing algorithm for SPW. We discuss the algorithm's generalization to other betting contexts, including betting on maximum/minimum and betting on the product of binary values. Finally, we describe a prototype we built to predict web site page views and discuss the implementation issues that arose.
Latent Fingerprint Matching: Fusion of Rolled and Plain Fingerprints
Authors: Jianjiang Feng, Soweon Yoon, Anil K. Jain
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Law enforcement agencies routinely collect both rolled and plain fingerprints of all the ten fingers of suspects. These two types of fingerprints complement each other, since rolled fingerprints are of larger size and contain more minutiae, and plain fingerprints are less affected by distortion and have clearer ridge structure. It is widely known in the law enforcement community that searching both rolled and plain fingerprints can improve the accuracy of latent matching, but, this does not appear to be a common practice in law enforcement. To our knowledge, only rank level fusion option is provided by the vendors. There has been no systematic study and comparison of different fusion techniques. In this paper, multiple fusion approaches at three different levels (rank, score and feature) are proposed to fuse rolled and plain fingerprints. Experimental results in searching 230 latents in the NIST SD27 against a database of 4,180 pairs of rolled and plain fingerprints show that most of the fusion approaches can improve the identification performance. The greatest improvement was obtained by boosted max fusion at the score level, which reaches a rank-1 identification rate of 83.0%, compared to the rank-1 rate of 57.8% for plain and 70.4% for rolled prints.
Rethinking Online Faculty Instructional Development: A Case Study
Authors: Shinn-Rong Lin, Yi-Chin Wu, Chia-Wen Liu, Hsiao-Ting Teng
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

This study elucidates issues generated by the Interactive Platform for Faculty Instructional Development (IPFID) website (http://140.115.107.44). The website content comprises real classroom observations for teaching analysis, presented with films and texts for faculty and student feedback, responses, and discussions. Five instructors who each won an Award of Excellence in Teaching were participants for classroom observations and teaching analysis on the IPFID website. This work is based on the analytical results for February 2006 to April 2007. The following three issues were discussed: lack of the responses from the faculty, time allocated by faculty, and the multiple faculty roles expected by the research university.
SAS High-Performance Forecasting 2.3: User's Guide
Venue:  (2007)

Documents the syntax of the High-Performance Forecasting product and demonstrates its use through examples. 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