ppxscal/embedding_network huggingface dataset:
Finding Frequent Items in a Turnstile Data Stream
Authors: Regant Y. Hung, Kwok Fai Lai, Hing Fung Ting
Venue: Proceedings of the 14th annual international conference on Computing and Combinatorics (2008)

Because of important applications such as denial-of-service attack detection, finding frequent items in data streams under different models has been studied extensively. Finding frequent items in a turnstile data stream is the most challenging because both insertions and deletions of items are allowed in the stream. In this paper, we propose a deterministic algorithm that solves the problem. Furthermore, we propose a randomized algorithm for the problem. Empirical results show that our randomized algorithm provides better results than existing randomized algorithms for the problem and our algorithm uses much smaller space, and supports faster query time and similar update time.
What Is the Lesson of Quantum Computing?
Authors: Christopher G. Timpson
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

It would be a mistake to seek for a single lesson that the advent of quantum computing has provided: the theory is rich in both physics and computer science terms. But my quarry is a, or perhaps the, central conceptual point that we should draw; and it concerns putative shifts in our understanding of the Church- Turing hypothesis inspired by reflection on quantum computation. 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
Generalization Bounds for Some Ordinal Regression Algorithms
Authors: Shivani Agarwal
Venue: Proceedings of the 19th international conference on Algorithmic Learning Theory (2008)

The problem of ordinal regression, in which the goal is to learn a rule to predict labels from a discrete but ordered set, has gained considerable attention in machine learning in recent years. We study generalization properties of algorithms for this problem. We start with the most basic algorithms that work by learning a real-valued function in a regression framework and then rounding off a predicted real value to the closest discrete label; our most basic bounds for such algorithms are derived by relating the ordinal regression error of the resulting prediction rule to the regression error of the learned real-valued function. We end with a margin-based bound for the state-of-the-art ordinal regression algorithm of Chu Keerthi (2007).
Did federal regulation discourage facilities-based entry into US local telecommunications markets?
Authors: Troy Quast
Venue: Telecommunications Policy (2008)

In the United States from 2001 to 2006, federal regulations allowed entrants to lease from incumbents at relatively low cost all of the network infrastructure necessary to provide local phone service. These platform entrants could then provide phone service without installing any of their own equipment. Advocates of this policy claimed that it was needed to provide an economically feasible means by which entrants could serve residential customers. Critics contended that the policy substantially deterred loop entry whereby entrants installed their own switching equipment. An analysis of panel data for each state over this period indicates that the policy's critics may have been correct. The cross-price elasticity of loop entry with respect to platform price was roughly 1.0. A back of the envelope calculation suggests that loop entry may have decreased by roughly 20% due to platform entry price reductions.
Pronto: Mobile Gateway With Publish-Subscribe Paradigm Over Wireless Network
Authors: Eiko Yoneki
Venue: IEEE Distributed Systems Online (2003)

Pronto, a messaging middleware system for mobile applications, provides both centralized and decentralized models. It addresses design issues in mobile computing, including data optimization and disconnected operation. Pronto consists of a lightweight message-oriented middleware (MOM) client and an intelligent gateway serving as a message hub with store-and-forward messaging.
Comparison of the SPEC CPU Benchmarks with 499 Other Workloads Using Hardware Counters
Authors: Lodewijk Bonebakker
Venue: Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks (2008)

This work extends an existing workload comparison approach used for simulation based metrics to computer system based metrics. We apply this approach using processor hardware counters and compare characterizations of spec cpu2000 and spec cpu2006, against real (commercial) workloads and other benchmarks collected on the same computer system architecture. Using Independent Component analysis we reduce the many dimensional workload characterization space into a lesser dimensional representative space prior to comparing the distribution of workloads. We find that the spec cpu benchmarks are for the most part representative on the identified principal components, with notable exceptions.
Framing Europe online: French political parties and the European election of 2004
Authors: Renèe van Os
Venue: Information Polity (2005)

In this article, the notion of Europeanization of political communication and the possible development of a European public sphere is explored. The article offers a concrete approach to investigating this notion with direct reference to the Internet. Specifically, I examine the unfolding of communicative interaction on the Web sites of French political parties in the context of the 2004 European Parliament election. Through their Web sites, parties offer a particular perspective on European news, issues and events, suggesting whether and why discrete issues broadly concerning Europe are (or should be) socially and politically relevant. Three interpretative frames, derived from theory, are examined in the paper: interests, identity and values. It was found that the three frames coexist in various sections of the Web sites within the French sample. Specifically, European interests and identity are usually expressed in combination with national interests and values. Universal values are frequently expressed, both in relation to France and the EU. Overall, the findings point to a general 'feeling of belonging to Europe' among a number of the French political parties included in the sample. These parties did, to a degree, communicate from a 'Europeanized' perspective.
A Two-Dimensional Entropic Approach to Intuitionistic Fuzzy Contrast Enhancement
Authors: Ioannis K. Vlachos, George D. Sergiadis
Venue: Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory (2007)

This paper presents a generalized approach to the intuitionistic fuzzification of gray-scale images. Parametric membership and non-membership functions are applied in order to derive the optimal representation of the image in the intuitionistic fuzzy domain. A two-dimensional intuitionistic fuzzy entropy measure is employed as the optimization criterion for driving the aforementioned procedure. Finally, experimental results demonstrate the ability of the proposed method to efficiently enhance low-contrasted gray-scale images.
Constrained Clustering Via Concavity Cuts
Authors: Yu Xia
Venue: Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2007)

In this paper, we adapt Tuy's concave cutting plane method to the problem of finding an optimal grouping of semi-supervised clustering. We also give properties of local optimal solutions to the semi-supervised clustering. On test data sets with up to 1500 points, our algorithm typically find a solution with objective value around 2% smaller of the initial function value than that obtained by k-means algorithm within 4 seconds, although the run time is hundred times of that of the k-means algorithm.
AND/OR Multi-valued Decision Diagrams for Constraint Networks
Authors: Robert Mateescu, Rina Dechter
Venue: Concurrency, Graphs and Models: Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday (2008)

The paper is an overview of a recently developed compilation data structure for graphical models, with specific application to constraint networks. The AND/OR Multi-Valued Decision Diagram (AOMDD) augments well known decision diagrams (OBDDs, MDDs) with AND nodes, in order to capture function decomposition structure. The AOMDD is based on a pseudo tree of the network, rather than a linear ordering of its variables. The AOMDD of a constraint network is a canonical form given a pseudo tree. We describe two main approaches for compiling the AOMDD of a constraint network. The first is a top down, search-based procedure, that works by applying reduction rules to the trace of the memory intensive AND/OR search algorithm. The second is a bottom up, inference-based procedure, that uses a Bucket Elimination schedule. For both algorithms, the compilation time and the size of the AOMDD are, in the worst case, exponential in the treewidth of the constraint graph, rather than pathwidth as is known for ordered binary decision diagrams (OBDDs).
Temporal Properties of Illusory-Surface Perception Probed with Poggendorff Configuration
Authors: Qin Wang, Marsanori Idesawa
Venue: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks (2008)

Temporal properties of illusory surface perception were investigated by using the probing method of the Poggendorff configuration. We used real lines and an opaque illusory surface to compose the Poggendorff configuration, which was presented in an intermittent display method so that the real lines were displayed continuously and the opaque illusory surface was displayed periodically with various duration and interval times. The results showed that the opaque illusory surface required a minimum duration of approximately 220 msec for sustained perception. An interval of as much as 2200 msec was needed to obliterate the perception of the opaque illusory surface. We decided the intermittent display method was effective to directly examine the time course of illusory surface perception. Furthermore, we concluded that we could achieve better understanding of the surface perception mechanism of the human visual system by utilizing the intermittent display method and probing method of the Poggendorff configuration.
A Methodology for Low-Cost Image Annotation Based on Conceptual Modeling: A Biological Example
Authors: Arnaud Da Costa, Éric Leclercq, Marinette Savonnet, Marie-Noëlle Terrasse
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

In the context of data-intensive biology applications the overall annotation costs are rather high since experts generally need to be involved. In some cases it is possible to automate the annotation process. In this paper we propose an approach that consists in building an image database application that enables domain technicians to make annotation swithout compromizing their semantical precision. Our proposal relies mainly on a domain ontology coupled with a conceptual data model.
Standard Specification for S-100 Bus Interface Devices
Authors: K. A. Elmquist
Venue: Computer (1979)

This proposed standard eliminates many of the problems in the S-100 bus and upgrades it for 16-bit microprocessors. It is offered here for public comment before submission to the IEEE Standards Board.
Allometric extension model for conditional distributions
Authors: Hiroshi Kurata, Takahiro Hoshino, Yasunori Fujikoshi
Venue: Journal of Multivariate Analysis (2008)

When two groups are present, they are said to form an allometric model, if one group is the extension of the other group along the main axis of variation. The model is widely used in the context of principal component analysis, especially for the description of growth processes of creatures. In this paper, the notion of allometric extension model is applied to conditional distributions. More specifically, we derive a sufficient condition, for which the two conditional distributions given the sign of the first principal component form an allometric extension model.
Toward Bridging the Annotation-Retrieval Gap in Image Search
Authors: Ritendra Datta, Weina Ge, Jia Li, James Z. Wang
Venue: IEEE MultiMedia (2007)

By combining novel statistical modeling techniques and the WordNet ontology, we offer a promising new approach to image search that uses automatic image tagging directly to perform retrieval.
Sequential local least squares imputation estimating missing value of microarray data
Authors: Xiaobai Zhang, Xiaofeng Song, Huinan Wang, Huanping Zhang
Venue: Computers in Biology and Medicine (2008)

Missing values in microarray data can significantly affect subsequent analysis, thus it is important to estimate these missing values accurately. In this paper, a sequential local least squares imputation (SLLSimpute) method is proposed to solve this problem. It estimates missing values sequentially from the gene containing the fewest missing values and partially utilizes these estimated values. In addition, an automatic parameter selection algorithm, which can generate an appropriate number of neighboring genes for each target gene, is presented for parameter estimation. Experimental results confirmed that SLLSimpute method exhibited better estimation ability compared with other currently used imputation methods.
Speaker Recognition Using Temporal Decomposition of LSF for Mobile Environment
Authors: Sung-Joo Kim, Min-Seok Kim, Ha-Jin Yu
Venue: Proceedings of the 3rd international conference on Embedded Software and Systems (2007)

A novel approach to speaker recognition in mobile or IP network environment is described. In this approach, we use decoded line spectral frequency (LSF) parameters directly from compressed speech packets instead of using parameters from decompression and analysis procedure. Furthermore, we reduce the number of LSF series based on a restricted temporal decomposition method. Consequently, proposed approach gets more than three times faster than a traditional speaker recognition approach without losing any accuracy according to our experiments.
Multi-root, Multi-Query Processing in Sensor Networks
Authors: Zhiguo Zhang, Ajay Kshemkalyani, Sol M. Shatz
Venue: Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems (2008)

Sensor networks can be viewed as large distributed databases, and SQL-like high-level declarative languages can be used for data and information retrieval. Energy constraints make optimizing query processing particularly important. This paper addresses for the first time, multi-root, multi-query optimization for long duration aggregation queries. The paper formulates three algorithms - naive algorithm (NMQ), which does not exploit any query result sharing, and two proposed new algorithms: an optimal algorithm (OMQ) and a heuristic (zone-based) algorithm (ZMQ). The heuristic algorithm is based on sharing the partially aggregated results of pre-configured geographic regions and exploits the novel idea of applying a grouping technique by using the location attribute of sensor nodes as the grouping criterion. Extensive simulations indicate that the proposed algorithms provide significant energy savings under a wide range of sensor network deployments and query region options.
Algorithms for center and Tverberg points
Authors: Pankaj K. Agarwal, Micha Sharir, Emo Welzl
Venue: ACM Transactions on Algorithms (TALG) (2008)

Given a set S of n points in R3, a point x in R3 is called center point of S if every closed halfspace whose bounding hyperplane passes through x contains at least &lceil;n/4&rceil; points from S. We present a near-quadratic algorithm for computing the center region, that is the set of all center points, of a set of n points in R3. This is nearly tight in the worst case since the center region can have &Omega;(n2) complexity. We then consider sets S of 3n points in the plane which are the union of three disjoint sets consisting respectively of n red, n blue, and n green points. A point x in R2 is called a colored Tverberg point of S if there is a partition of S into n triples with one point of each color, so that x lies in all triangles spanned by these triples. We present a first polynomial-time algorithm for recognizing whether a given point is a colored Tverberg point of such a 3-colored set S.
Techniques for peer-to-peer content distribution over mobile ad hoc networks
Authors: C.-C. Jay Kuo
Venue:  (2007)

The mobile ad-hoc network (MANET) is emerging as a new paradigm of wireless communication in both civilian and military applications. Recently, efforts have been made to migrate peer-to-peer (P2P) applications from the wired Internet to the MANET system, which are expected to be the major impetus to MANET commercialization. Several fundamental technologies that facilitate the deployment of P2P content distribution systems over MANET are investigated. In particular, we have focused on efficient P2P content discovery and privacy protection in P2P file sharing. First, a Bloom filter (BF)-based probabilistic routing (VABF) is proposed to improve query efficiency. The VABF protocol constructs its routing tables using Bloom filters in a distributed manner without the knowledge of the global network. Each node forwards P2P queries to its closest object holders by the shortest path. Simulation results show that VABF outperforms several popular unstructured P2P search algorithms in terms of the query success rate and the route strength. Second, the performance of several unstructured P2P content discovery techniques over MANETs is analyzed. They include: query flooding, expanding ring search, random walk and BF-based probabilistic routing. The chosen performance metrics are the query success rate, the route stretch and the search cost. Mathematic analysis is conducted to predict their behavior in static networks. Besides, the overhead introduced by the BF-based probabilistic routing is modeled using a M/G/&infin; queue. Finally, extensive computer simulation is performed to validate our analytical results in a static environment and shed light on the behavior of these schemes in a mobile environment. Third, the MANET Anonymous Peer-to-peer Communication Protocol (MAPCP) is proposed for privacy protection. MAPCP uses broadcasts with probabilistic flooding control to establish multiple anonymous paths between communication peers. It requires no hop-by-hop encryption/decryption along anonymous paths and builds multiple paths to multiple peers within a single query phase without using an extra route discovery process. The analysis and simulations show that MAPCP always maintains a higher degree of anonymity than a MANET anonymous single-path routing protocol in a hostile environment.
Collaborative Ranking: An Aggregation Algorithm for Individuals' Preference Estimation
Authors: Joachim Giesen, Dieter Mitsche, Eva Schuberth
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

We consider the problem of estimating an individual's product preferences for substitute goods or services. The preferences are elicited by questionnaires that pose a few choice tasks to individuals from the population (respondents). The simplest choice task is a pairwise comparison. To elicit a respondent's ranking of n products completely ¿(nlogn) pairwise comparisons are necessary. These are easily too many in settings where the incentive for the respondent is not high though he might be willing to answer a few questions truthfully. One approach to cope with this complexity is to aggregate the answers of several respondents in order to estimate an individual's complete preference ranking. Here we describe such an aggregation mechanism based on spectral clustering and prove its validity in statistical model of population and respondents.
On Radio Broadcasting in Random Geometric Graphs
Authors: Robert Elsässer, Leszek Gąsieniec, Thomas Sauerwald
Venue: Proceedings of the 22nd international symposium on Distributed Computing (2008)

One of the most frequently studied problems in the context of information dissemination in communication networks is the broadcasting problem. In this paper we consider radio broadcasting in random geometric graphs, in which n nodes are placed uniformly at random in $[0, \sqrt{n}]^2$, and there is a (directed) edge from a node u to a node v in the corresponding graph iff the distance between u and v is smaller than the transmission radius assigned to u. Throughout this paper we consider the distributed case, i.e., each node is only aware (apart from n) of its own coordinates and its own transmission radius, and we assume that the transmission radii of the nodes vary according to a power law distribution. First, we consider the model in which any node is assigned a transmission radius r > r min according to a probability density function ρ(r) ~r ¿ ¿ (more precisely, $\rho(r) = (\alpha-1)r_{\min}^{\alpha-1} r^{-\alpha}$), where ¿ ¿ (1,3) and $r_{\min}> \delta \sqrt{\log n}$ with ¿ being a large constant. For this case, we develop a simple radio broadcasting algorithm which has the running time O(loglogn), with high probability, and show that this result is asymptotically optimal. Then, we consider the model in which any node is assigned a transmission radius r > c according to the probability density function ρ(r) = (¿ ¿ 1)c ¿¿ 1 r ¿ ¿ , where ¿ is drawn from the same range as before and c is a constant. Since this graph is usually not strongly connected, we assume that the message which has to be spread to all nodes of the graph is placed initially in one of the nodes of the giant component. We show that there exists a fully distributed randomized algorithm which disseminates the message in O(D (loglogn)2) steps, with high probability, where D denotes the diameter of the giant component of the graph.Our results imply that by setting the transmission radii of the nodes according to a power law distribution, one can design energy efficient radio networks with low average transmission radius, in which broadcasting can be performed exponentially faster than in the (extensively studied) case where all nodes have the same transmission power.
Can quantum mechanics help distributed computing?
Authors: Anne Broadbent, Alain Tapp
Venue: ACM SIGACT News (2008)

We present a brief survey of results where quantum information processing is useful to solve distributed computation tasks. We describe problems that are impossible to solve using classical resources but that become feasible with the help of quantum mechanics. We also give examples where the use of quantum information significantly reduces the need for communication. The main focus of the survey is on communication complexity but we also address other distributed tasks.