OpenRaiser/Intern-Atlas huggingface dataset:
Faceted Ranking of Egos in Collaborative Tagging Systems
Venue: arXiv cs.IR 2008
Year: 2008

Multimedia uploaded content is tagged and recommended by users of collaborative systems, resulting in informal classifications also known as folksonomies. Faceted web ranking has been proved a reasonable alternative to a single ranking which does not take into account a personalized context. In this paper we analyze the online computation of rankings of users associated to facets made up of multiple tags. Possible applications are user reputation evaluation (ego-ranking) and improvement of content quality in case of retrieval. We propose a solution based on PageRank as centrality measure: (i) a ranking for each tag is computed offline on the basis of the corresponding tag-dependent subgraph; (ii) a faceted order is generated by merging rankings corresponding to all the tags in the facet. The fundamental assumption, validated by empirical observations, is that step (i) is scalable. We also present algorithms for part (ii) having time complexity O(k), where k is the number of tags in the facet, well suited to online computation.
The Imaginary Sliding Window As a New Data Structure for Adaptive Algorithms
Venue: arXiv cs.IT 2008
Year: 2008

The scheme of the sliding window is known in Information Theory, Computer Science, the problem of predicting and in stastistics. Let a source with unknown statistics generate some word $... x_{-1}x_{0}x_{1}x_{2}...$ in some alphabet $A$. For every moment $t, t=... $ $-1, 0, 1, ...$, one stores the word ("window") $ x_{t-w} x_{t-w+1}... x_{t-1}$ where $w$,$w \geq 1$, is called "window length". In the theory of universal coding, the code of the $x_{t}$ depends on source ststistics estimated by the window, in the problem of predicting, each letter $x_{t}$ is predicted using information of the window, etc. After that the letter $x_{t}$ is included in the window on the right, while $x_{t-w}$ is removed from the window. It is the sliding window scheme. This scheme has two merits: it allows one i) to estimate the source statistics quite precisely and ii) to adapt the code in case of a change in the source' statistics. However this scheme has a defect, namely, the necessity to store the window (i.e. the word $x_{t-w}... x_{t-1})$ which needs a large memory size for large $w$. A new scheme named "the Imaginary Sliding Window (ISW)" is constructed. The gist of this scheme is that not the last element $x_{t-w}$ but rather a random one is removed from the window. This allows one to retain both merits of the sliding window as well as the possibility of not storing the window and thus significantly decreasing the memory size.
Efficient, Differentially Private Point Estimators
Venue: arXiv cs.CR 2008
Year: 2008

Differential privacy is a recent notion of privacy for statistical databases that provides rigorous, meaningful confidentiality guarantees, even in the presence of an attacker with access to arbitrary side information. We show that for a large class of parametric probability models, one can construct a differentially private estimator whose distribution converges to that of the maximum likelihood estimator. In particular, it is efficient and asymptotically unbiased. This result provides (further) compelling evidence that rigorous notions of privacy in statistical databases can be consistent with statistically valid inference.
Performance-Aware Power Management in Embedded Controllers with Multiple-Voltage Processors
Venue: arXiv cs.OH 2008
Year: 2008

The goal of this work is to minimize the energy dissipation of embedded controllers without jeopardizing the quality of control (QoC). Taking advantage of the dynamic voltage scaling (DVS) technology, this paper develops a performance-aware power management scheme for embedded controllers with processors that allow multiple voltage levels. The periods of control tasks are adapted online with respect to the current QoC, thus facilitating additional energy reduction over standard DVS. To avoid the waste of CPU resources as a result of the discrete voltage levels, a resource reclaiming mechanism is employed to maximize the CPU utilization and also to improve the QoC. Simulations are conducted to evaluate the performance of the proposed scheme. Compared with the optimal standard DVS scheme, the proposed scheme is shown to be able to save remarkably more energy while maintaining comparable QoC.
Hybrid Neural Network Architecture for On-Line Learning
Venue: arXiv cs.NE 2008
Year: 2008

Approaches to machine intelligence based on brain models have stressed the use of neural networks for generalization. Here we propose the use of a hybrid neural network architecture that uses two kind of neural networks simultaneously: (i) a surface learning agent that quickly adapt to new modes of operation; and, (ii) a deep learning agent that is very accurate within a specific regime of operation. The two networks of the hybrid architecture perform complementary functions that improve the overall performance. The performance of the hybrid architecture has been compared with that of back-propagation perceptrons and the CC and FC networks for chaotic time-series prediction, the CATS benchmark test, and smooth function approximation. It has been shown that the hybrid architecture provides a superior performance based on the RMS error criterion.
A novel channel estimation based on spread pilots for terrestrial digital video broadcasting
Venue: arXiv cs.NI 2008
Year: 2008

In this paper, we propose a novel channel estimation technique based on spread pilots for digital video broadcasting. This technique consists in adding a linear preceding function before the OFDM modulation and dedicating one of the preceding sequence to transmit the pilot symbols for the channel estimation. The merits of this technique are its simplicity, its flexibility, and the gains in terms of spectral efficiency and useful bit rate obtained compared to the classical pilot based estimation schemes used in DVB standards. The performance evaluated over realistic channel models, shows the efficiency of this technique which turns out to be a promising channel estimation technique for the future terrestrial video broadcasting systems.
A Coded Bit-Loading Linear Precoded Discrete Multitone Solution for Power Line Communication
Venue: arXiv cs.IT 2008
Year: 2008

Linear precoded discrete multitone modulation (LP-DMT) system has been already proved advantageous with adaptive resource allocation algorithm in a power line communication (PLC) context. In this paper, we investigate the bit and energy allocation algorithm of an adaptive LP-DMT system taking into account the channel coding scheme. A coded adaptive LP-DMT system is presented in the PLC context with a loading algorithm which ccommodates the channel coding gains in bit and energy calculations. The performance of a concatenated channel coding scheme, consisting of an inner Wei's 4-dimensional 16-states trellis code and an outer Reed-Solomon code, in combination with the roposed algorithm is analyzed. Simulation results are presented for a fixed target bit error rate in a multicarrier scenario under power spectral density constraint. Using a multipath model of PLC channel, it is shown that the proposed coded adaptive LP-DMT system performs better than classical coded discrete multitone.
Coded Adaptive Linear Precoded Discrete Multitone Over PLC Channel
Venue: arXiv cs.IT 2008
Year: 2008

Discrete multitone modulation (DMT) systems exploit the capabilities of orthogonal subcarriers to cope efficiently with narrowband interference, high frequency attenuations and multipath fadings with the help of simple equalization filters. Adaptive linear precoded discrete multitone (LP-DMT) system is based on classical DMT, combined with a linear precoding component. In this paper, we investigate the bit and energy allocation algorithm of an adaptive LP-DMT system taking into account the channel coding scheme. A coded adaptive LPDMT system is presented in the power line communication (PLC) context with a loading algorithm which accommodates the channel coding gains in bit and energy calculations. The performance of a concatenated channel coding scheme, consisting of an inner Wei's 4-dimensional 16-states trellis code and an outer Reed-Solomon code, in combination with the proposed algorithm is analyzed. Theoretical coding gains are derived and simulation results are presented for a fixed target bit error rate in a multicarrier scenario under power spectral density constraint. Using a multipath model of PLC channel, it is shown that the proposed coded adaptive LP-DMT system performs better than coded DMT and can achieve higher throughput for PLC applications.
Determining the Unithood of Word Sequences using a Probabilistic Approach
Venue: arXiv cs.AI 2008
Year: 2008

Most research related to unithood were conducted as part of a larger effort for the determination of termhood. Consequently, novelties are rare in this small sub-field of term extraction. In addition, existing work were mostly empirically motivated and derived. We propose a new probabilistically-derived measure, independent of any influences of termhood, that provides dedicated measures to gather linguistic evidence from parsed text and statistical evidence from Google search engine for the measurement of unithood. Our comparative study using 1,825 test cases against an existing empirically-derived function revealed an improvement in terms of precision, recall and accuracy.
Optimization of sequences in CDMA systems: a statistical-mechanics approach
Venue: arXiv cs.IT 2008
Year: 2008

Statistical mechanics approach is useful not only in analyzing macroscopic system performance of wireless communication systems, but also in discussing design problems of wireless communication systems. In this paper, we discuss a design problem of spreading sequences in code-division multiple-access (CDMA) systems, as an example demonstrating the usefulness of statistical mechanics approach. We analyze, via replica method, the average mutual information between inputs and outputs of a randomly-spread CDMA channel, and discuss the optimization problem with the average mutual information as a measure of optimization. It has been shown that the average mutual information is maximized by orthogonally-invariant random Welch bound equality (WBE) spreading sequences.
Determining the Unithood of Word Sequences using Mutual Information and Independence Measure
Venue: arXiv cs.AI 2008
Year: 2008

Most works related to unithood were conducted as part of a larger effort for the determination of termhood. Consequently, the number of independent research that study the notion of unithood and produce dedicated techniques for measuring unithood is extremely small. We propose a new approach, independent of any influences of termhood, that provides dedicated measures to gather linguistic evidence from parsed text and statistical evidence from Google search engine for the measurement of unithood. Our evaluations revealed a precision and recall of 98.68% and 91.82% respectively with an accuracy at 95.42% in measuring the unithood of 1005 test cases.
A Fast Generic Sequence Matching Algorithm
Venue: arXiv cs.DS 2008
Year: 2008

A string matching -- and more generally, sequence matching -- algorithm is presented that has a linear worst-case computing time bound, a low worst-case bound on the number of comparisons (2n), and sublinear average-case behavior that is better than that of the fastest versions of the Boyer-Moore algorithm. The algorithm retains its efficiency advantages in a wide variety of sequence matching problems of practical interest, including traditional string matching; large-alphabet problems (as in Unicode strings); and small-alphabet, long-pattern problems (as in DNA searches). Since it is expressed as a generic algorithm for searching in sequences over an arbitrary type T, it is well suited for use in generic software libraries such as the C++ Standard Template Library. The algorithm was obtained by adding to the Knuth-Morris-Pratt algorithm one of the pattern-shifting techniques from the Boyer-Moore algorithm, with provision for use of hashing in this technique. In situations in which a hash function or random access to the sequences is not available, the algorithm falls back to an optimized version of the Knuth-Morris-Pratt algorithm.
Enhanced Integrated Scoring for Cleaning Dirty Texts
Venue: arXiv cs.AI 2008
Year: 2008

An increasing number of approaches for ontology engineering from text are gearing towards the use of online sources such as company intranet and the World Wide Web. Despite such rise, not much work can be found in aspects of preprocessing and cleaning dirty texts from online sources. This paper presents an enhancement of an Integrated Scoring for Spelling error correction, Abbreviation expansion and Case restoration (ISSAC). ISSAC is implemented as part of a text preprocessing phase in an ontology engineering system. New evaluations performed on the enhanced ISSAC using 700 chat records reveal an improved accuracy of 98% as compared to 96.5% and 71% based on the use of only basic ISSAC and of Aspell, respectively.
Definition and Implementation of a Points-To Analysis for C-like Languages
Venue: arXiv cs.PL 2008
Year: 2008

The points-to problem is the problem of determining the possible run-time targets of pointer variables and is usually considered part of the more general aliasing problem, which consists in establishing whether and when different expressions can refer to the same memory address. Aliasing information is essential to every tool that needs to reason about the semantics of programs. However, due to well-known undecidability results, for all interesting languages that admit aliasing, the exact solution of nontrivial aliasing problems is not generally computable. This work focuses on approximated solutions to this problem by presenting a store-based, flow-sensitive points-to analysis, for applications in the field of automated software verification. In contrast to software testing procedures, which heuristically check the program against a finite set of executions, the methods considered in this work are static analyses, where the computed results are valid for all the possible executions of the analyzed program. We present a simplified programming language and its execution model; then an approximated execution model is developed using the ideas of abstract interpretation theory. Finally, the soundness of the approximation is formally proved. The aim of developing a realistic points-to analysis is pursued by presenting some extensions to the initial simplified model and discussing the correctness of their formulation. This work contains original contributions to the issue of points-to analysis, as it provides a formulation of a filter operation on the points-to abstract domain and a formal proof of the soundness of the defined abstract operations: these, as far as we now, are lacking from the previous literature.
Condition Numbers of Gaussian Random Matrices
Venue: arXiv cs.NA 2008
Year: 2008

Let $G_{m \times n}$ be an $m \times n$ real random matrix whose elements are independent and identically distributed standard normal random variables, and let $κ_2(G_{m \times n})$ be the 2-norm condition number of $G_{m \times n}$. We prove that, for any $m \geq 2$, $n \geq 2$ and $x \geq |n-m|+1$, $κ_2(G_{m \times n})$ satisfies $ \frac{1}{\sqrt{2π}} ({c}/{x})^{|n-m|+1} < P(\frac{κ_2(G_{m \times n})} {{n}/{(|n-m|+1)}}> x) < \frac{1}{\sqrt{2π}} ({C}/{x})^{|n-m|+1}, $ where $0.245 \leq c \leq 2.000$ and $ 5.013 \leq C \leq 6.414$ are universal positive constants independent of $m$, $n$ and $x$. Moreover, for any $m \geq 2$ and $n \geq 2$, $ E(\logκ_2(G_{m \times n})) < \log \frac{n}{|n-m|+1} + 2.258. $ A similar pair of results for complex Gaussian random matrices is also established.
Bias-Variance Techniques for Monte Carlo Optimization: Cross-validation for the CE Method
Venue: arXiv cs.NA 2008
Year: 2008

In this paper, we examine the CE method in the broad context of Monte Carlo Optimization (MCO) and Parametric Learning (PL), a type of machine learning. A well-known overarching principle used to improve the performance of many PL algorithms is the bias-variance tradeoff. This tradeoff has been used to improve PL algorithms ranging from Monte Carlo estimation of integrals, to linear estimation, to general statistical estimation. Moreover, as described by, MCO is very closely related to PL. Owing to this similarity, the bias-variance tradeoff affects MCO performance, just as it does PL performance. In this article, we exploit the bias-variance tradeoff to enhance the performance of MCO algorithms. We use the technique of cross-validation, a technique based on the bias-variance tradeoff, to significantly improve the performance of the Cross Entropy (CE) method, which is an MCO algorithm. In previous work we have confirmed that other PL techniques improve the perfomance of other MCO algorithms. We conclude that the many techniques pioneered in PL could be investigated as ways to improve MCO algorithms in general, and the CE method in particular.
Maximally Radio-Disjoint Multipath Routing for Wireless Multimedia Sensor Networks
Venue: arXiv cs.NI 2008
Year: 2008

In wireless sensor networks, bandwidth is one of precious resources to multimedia applications. To get more bandwidth, multipath routing is one appropriate solution provided that inter-path interferences are minimized. In this paper, we address the problem of interfering paths in the context of wireless multimedia sensor networks and consider both intra-session as well as inter-session interferences. Our main objective is to provide necessary bandwidth to multimedia applications through non-interfering paths while increasing the network lifetime. To do so, we adopt an incremental approach where for a given session, only one path is built at once. Additional paths are built when required, typically in case of congestion or bandwidth shortage. Interference awareness and energy saving are achieved by switching a subset of sensor nodes in a {\em passive state} in which they do not take part in the routing process. Despite the routing overhead introduced by the incremental approach we adopt, our simulations show that this can be compensated by the overall achieved throughput and the amount of consumed energy per correctly received packet especially for relatively long sessions such as multimedia ones. This is mainly due to the fact that a small number of non-interfering paths allows for better performances than a large number of interfering ones.
Rate and Power Allocation in Fading Multiple Access Channels
Venue: arXiv cs.IT 2008
Year: 2008

We consider the problem of rate and power allocation in a fading multiple-access channel. Our objective is to obtain rate and power allocation policies that maximize a utility function defined over average transmission rates. In contrast with the literature, which focuses on the linear case, we present results for general concave utility functions. We consider two cases. In the first case, we assume that power control is possible and channel statistics are known. In this case, we show that the optimal policies can be obtained greedily by maximizing a linear utility function at each channel state. In the second case, we assume that power control is not possible and channel statistics are not available. In this case, we define a greedy rate allocation policy and provide upper bounds on the performance difference between the optimal and the greedy policy. Our bounds highlight the dependence of the performance difference on the channel variations and the structure of the utility function.
Information Theory vs. Queueing Theory for Resource Allocation in Multiple Access Channels
Venue: arXiv cs.IT 2008
Year: 2008

We consider the problem of rate allocation in a fading Gaussian multiple-access channel with fixed transmission powers. The goal is to maximize a general concave utility function of the expected achieved rates of the users. There are different approaches to this problem in the literature. From an information theoretic point of view, rates are allocated only by using the channel state information. The queueing theory approach utilizes the global queue-length information for rate allocation to guarantee throughput optimality as well as maximizing a utility function of the rates. In this work, we make a connection between these two approaches by showing that the information theoretic capacity region of a multiple-access channel and its stability region are equivalent. Moreover, our numerical results show that a simple greedy policy which does not use the queue-length information can outperform queue-length based policies in terms of convergence rate and fairness.
"Real" Slepian-Wolf Codes
Venue: arXiv cs.IT 2008
Year: 2008

We provide a novel achievability proof of the Slepian-Wolf theorem for i.i.d. sources over finite alphabets. We demonstrate that random codes that are linear over the real field achieve the classical Slepian-Wolf rate-region. For finite alphabets we show that typicality decoding is equivalent to solving an integer program. Minimum entropy decoding is also shown to achieve exponentially small probability of error. The techniques used may be of independent interest for code design for a wide class of information theory problems, and for the field of compressed sensing.
An Evidential Path Logic for Multi-Relational Networks
Venue: arXiv cs.LO 2008
Year: 2008

Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Description Framework (RDF). One of the primary purposes of a knowledge network is to reason; that is, to alter the topology of the network according to an algorithm that uses the existing topological structure as its input. There exist many such reasoning algorithms. With respect to the Semantic Web, the bivalent, monotonic reasoners of the RDF Schema (RDFS) and the Web Ontology Language (OWL) are the most prevalent. However, nothing prevents other forms of reasoning from existing in the Semantic Web. This article presents a non-bivalent, non-monotonic, evidential logic and reasoner that is an algebraic ring over a multi-relational network equipped with two binary operations that can be composed to execute various forms of inference. Given its multi-relational grounding, it is possible to use the presented evidential framework as another method for structuring knowledge and reasoning in the Semantic Web. The benefits of this framework are that it works with arbitrary, partial, and contradictory knowledge while, at the same time, it supports a tractable approximate reasoning process.
An Analytical Model of Information Dissemination for a Gossip-based Protocol
Venue: arXiv cs.DC 2008
Year: 2008

We develop an analytical model of information dissemination for a gossiping protocol that combines both pull and push approaches. With this model we analyse how fast an item is replicated through a network, and how fast the item spreads in the network, and how fast the item covers the network. We also determine the optimal size of the exchange buffer, to obtain fast replication. Our results are confirmed by large-scale simulation experiments.
Liouvillian Solutions of Difference-Differential Equations
Venue: arXiv cs.SC 2008
Year: 2008

For a field k$with an automorphism σand a derivation δ, we introduce the notion of liouvillian solutions of linear difference-differential systems {σ(Y) = AY, δ(Y) = BY} over k and characterize the existence of liouvillian solutions in terms of the Galois group of the systems. We will give an algorithm to decide whether such a system has liouvillian solutions when k = C(x,t), σ(x) = x+1, δ= d/dt$ and the size of the system is a prime.