OpenRaiser/Intern-Atlas huggingface dataset:
Pricing strategies for viral marketing on Social Networks
Venue: arXiv cs.DS 2009
Year: 2009

We study the use of viral marketing strategies on social networks to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optimal strategy in a wide variety of models. The strategy is based on an influence-and-exploit idea, and it consists of finding the right trade-off at each time step between: generating revenue from the current user versus offering the product for free and using the influence generated from this sale later in the process. We also show how local search can be used to improve the performance of this technique in practice.
A Systematic Approach to Artificial Agents
Venue: arXiv cs.AI 2009
Year: 2009

Agents and agent systems are becoming more and more important in the development of a variety of fields such as ubiquitous computing, ambient intelligence, autonomous computing, intelligent systems and intelligent robotics. The need for improvement of our basic knowledge on agents is very essential. We take a systematic approach and present extended classification of artificial agents which can be useful for understanding of what artificial agents are and what they can be in the future. The aim of this classification is to give us insights in what kind of agents can be created and what type of problems demand a specific kind of agents for their solution.
Uniqueness of Low-Rank Matrix Completion by Rigidity Theory
Venue: arXiv cs.LG 2009
Year: 2009

The problem of completing a low-rank matrix from a subset of its entries is often encountered in the analysis of incomplete data sets exhibiting an underlying factor model with applications in collaborative filtering, computer vision and control. Most recent work had been focused on constructing efficient algorithms for exact or approximate recovery of the missing matrix entries and proving lower bounds for the number of known entries that guarantee a successful recovery with high probability. A related problem from both the mathematical and algorithmic point of view is the distance geometry problem of realizing points in a Euclidean space from a given subset of their pairwise distances. Rigidity theory answers basic questions regarding the uniqueness of the realization satisfying a given partial set of distances. We observe that basic ideas and tools of rigidity theory can be adapted to determine uniqueness of low-rank matrix completion, where inner products play the role that distances play in rigidity theory. This observation leads to an efficient randomized algorithm for testing both local and global unique completion. Crucial to our analysis is a new matrix, which we call the completion matrix, that serves as the analogue of the rigidity matrix.
Sparse Recovery of Positive Signals with Minimal Expansion
Venue: arXiv cs.IT 2009
Year: 2009

We investigate the sparse recovery problem of reconstructing a high-dimensional non-negative sparse vector from lower dimensional linear measurements. While much work has focused on dense measurement matrices, sparse measurement schemes are crucial in applications, such as DNA microarrays and sensor networks, where dense measurements are not practically feasible. One possible construction uses the adjacency matrices of expander graphs, which often leads to recovery algorithms much more efficient than $\ell_1$ minimization. However, to date, constructions based on expanders have required very high expansion coefficients which can potentially make the construction of such graphs difficult and the size of the recoverable sets small. In this paper, we construct sparse measurement matrices for the recovery of non-negative vectors, using perturbations of the adjacency matrix of an expander graph with much smaller expansion coefficient. We present a necessary and sufficient condition for $\ell_1$ optimization to successfully recover the unknown vector and obtain expressions for the recovery threshold. For certain classes of measurement matrices, this necessary and sufficient condition is further equivalent to the existence of a "unique" vector in the constraint set, which opens the door to alternative algorithms to $\ell_1$ minimization. We further show that the minimal expansion we use is necessary for any graph for which sparse recovery is possible and that therefore our construction is tight. We finally present a novel recovery algorithm that exploits expansion and is much faster than $\ell_1$ optimization. Finally, we demonstrate through theoretical bounds, as well as simulation, that our method is robust to noise and approximate sparsity.
On graph theoretic results underlying the analysis of consensus in multi-agent systems
Venue: arXiv cs.MA 2009
Year: 2009

This note corrects a pretty serious mistake and some inaccuracies in "Consensus and cooperation in networked multi-agent systems" by R. Olfati-Saber, J.A. Fax, and R.M. Murray, published in Vol. 95 of the Proceedings of the IEEE (2007, No. 1, P. 215-233). It also mentions several stronger results applicable to the class of problems under consideration and addresses the issue of priority whose interpretation in the above-mentioned paper is not exact.
Constant-Weight and Constant-Charge Binary Run-Length Limited Codes
Venue: arXiv cs.IT 2009
Year: 2009

Constant-weight and constant-charge binary sequences with constrained run length of zeros are introduced. For these sequences, the weight and the charge distribution are found. Then, recurrent and direct formulas for calculating the number of these sequences are obtained. With considering these numbers of constant-weight and constant-charge RLL sequences as coefficients of convergent power series, generating functions are derived. The fact, that generating function for enumerating constant-charge RLL sequences does not have a closed form, is proved. Implementation of encoding and decoding procedures using Cover's enumerative scheme is shown. On the base of obtained results, some examples, such as enumeration of running-digital-sum (RDS) constrained RLL sequences or peak-shifts control capability are also provided.
Percolation Processes and Wireless Network Resilience to Degree-Dependent and Cascading Node Failures
Venue: arXiv cs.NI 2009
Year: 2009

We study the problem of wireless network resilience to node failures from a percolation-based perspective. In practical wireless networks, it is often the case that the failure probability of a node depends on its degree (number of neighbors). We model this phenomenon as a degree-dependent site percolation process on random geometric graphs. In particular, we obtain analytical conditions for the existence of phase transitions within this model. Furthermore, in networks carrying traffic load, the failure of one node can result in redistribution of the load onto other nearby nodes. If these nodes fail due to excessive load, then this process can result in a cascading failure. Using a simple but descriptive model, we show that the cascading failure problem for large-scale wireless networks is equivalent to a degree-dependent site percolation on random geometric graphs. We obtain analytical conditions for cascades in this model.
Connectivity, Percolation, and Information Dissemination in Large-Scale Wireless Networks with Dynamic Links
Venue: arXiv cs.IT 2009
Year: 2009

We investigate the problem of disseminating broadcast messages in wireless networks with time-varying links from a percolation-based perspective. Using a model of wireless networks based on random geometric graphs with dynamic on-off links, we show that the delay for disseminating broadcast information exhibits two behavioral regimes, corresponding to the phase transition of the underlying network connectivity. When the dynamic network is in the subcritical phase, ignoring propagation delays, the delay scales linearly with the Euclidean distance between the sender and the receiver. When the dynamic network is in the supercritical phase, the delay scales sub-linearly with the distance. Finally, we show that in the presence of a non-negligible propagation delay, the delay for information dissemination scales linearly with the Euclidean distance in both the subcritical and supercritical regimes, with the rates for the linear scaling being different in the two regimes.
Lightweight Task Analysis for Cache-Aware Scheduling on Heterogeneous Clusters
Venue: arXiv cs.DC 2009
Year: 2009

We present a novel characterization of how a program stresses cache. This characterization permits fast performance prediction in order to simulate and assist task scheduling on heterogeneous clusters. It is based on the estimation of stack distance probability distributions. The analysis requires the observation of a very small subset of memory accesses, and yields a reasonable to very accurate prediction in constant time.
Dynamic Conjectures in Random Access Networks Using Bio-inspired Learning
Venue: arXiv cs.GT 2009
Year: 2009

This paper considers a conjecture-based distributed learning approach that enables autonomous nodes to independently optimize their transmission probabilities in random access networks. We model the interaction among multiple self-interested nodes as a game. It is well-known that the Nash equilibria in this game result in zero throughput for all the nodes if they take myopic best-response, thereby leading to a network collapse. This paper enables nodes to behave as intelligent entities which can proactively gather information, form internal conjectures on how their competitors would react to their actions, and update their beliefs according to their local observations. In this way, nodes are capable to autonomously "learn" the behavior of their competitors, optimize their own actions, and eventually cultivate reciprocity in the random access network. To characterize the steady-state outcome, the conjectural equilibrium is introduced. Inspired by the biological phenomena of "derivative action" and "gradient dynamics", two distributed conjecture-based action update mechanisms are proposed to stabilize the random access network. The sufficient conditions that guarantee the proposed conjecture-based learning algorithms to converge are derived. Moreover, it is shown that all the achievable operating points in the throughput region are essentially stable conjectural equilibria corresponding to different conjectures. We investigate how the conjectural equilibrium can be selected in heterogeneous networks and how the proposed methods can be extended to ad-hoc networks. Simulations verify that the system performance significantly outperforms existing protocols, such as IEEE 802.11 DCF protocol and the PMAC protocol, in terms of throughput, fairness, convergence, and stability.
Range and Roots: Two Common Patterns for Specifying and Propagating Counting and Occurrence Constraints
Venue: arXiv cs.AI 2009
Year: 2009

We propose Range and Roots which are two common patterns useful for specifying a wide range of counting and occurrence constraints. We design specialised propagation algorithms for these two patterns. Counting and occurrence constraints specified using these patterns thus directly inherit a propagation algorithm. To illustrate the capabilities of the Range and Roots constraints, we specify a number of global constraints taken from the literature. Preliminary experiments demonstrate that propagating counting and occurrence constraints using these two patterns leads to a small loss in performance when compared to specialised global constraints and is competitive with alternative decompositions using elementary constraints.
Filtering Algorithms for the Multiset Ordering Constraint
Venue: arXiv cs.AI 2009
Year: 2009

Constraint programming (CP) has been used with great success to tackle a wide variety of constraint satisfaction problems which are computationally intractable in general. Global constraints are one of the important factors behind the success of CP. In this paper, we study a new global constraint, the multiset ordering constraint, which is shown to be useful in symmetry breaking and searching for leximin optimal solutions in CP. We propose efficient and effective filtering algorithms for propagating this global constraint. We show that the algorithms are sound and complete and we discuss possible extensions. We also consider alternative propagation methods based on existing constraints in CP toolkits. Our experimental results on a number of benchmark problems demonstrate that propagating the multiset ordering constraint via a dedicated algorithm can be very beneficial.
The Parameterized Complexity of Global Constraints
Venue: arXiv cs.AI 2009
Year: 2009

We argue that parameterized complexity is a useful tool with which to study global constraints. In particular, we show that many global constraints which are intractable to propagate completely have natural parameters which make them fixed-parameter tractable and which are easy to compute. This tractability tends either to be the result of a simple dynamic program or of a decomposition which has a strong backdoor of bounded size. This strong backdoor is often a cycle cutset. We also show that parameterized complexity can be used to study other aspects of constraint programming like symmetry breaking. For instance, we prove that value symmetry is fixed-parameter tractable to break in the number of symmetries. Finally, we argue that parameterized complexity can be used to derive results about the approximability of constraint propagation.
SLIDE: A Useful Special Case of the CARDPATH Constraint
Venue: arXiv cs.AI 2009
Year: 2009

We study the CardPath constraint. This ensures a given constraint holds a number of times down a sequence of variables. We show that SLIDE, a special case of CardPath where the slid constraint must hold always, can be used to encode a wide range of sliding sequence constraints including CardPath itself. We consider how to propagate SLIDE and provide a complete propagator for CardPath. Since propagation is NP-hard in general, we identify special cases where propagation takes polynomial time. Our experiments demonstrate that using SLIDE to encode global constraints can be as efficient and effective as specialised propagators.
Reformulating Global Grammar Constraints
Venue: arXiv cs.AI 2009
Year: 2009

An attractive mechanism to specify global constraints in rostering and other domains is via formal languages. For instance, the Regular and Grammar constraints specify constraints in terms of the languages accepted by an automaton and a context-free grammar respectively. Taking advantage of the fixed length of the constraint, we give an algorithm to transform a context-free grammar into an automaton. We then study the use of minimization techniques to reduce the size of such automata and speed up propagation. We show that minimizing such automata after they have been unfolded and domains initially reduced can give automata that are more compact than minimizing before unfolding and reducing. Experimental results show that such transformations can improve the size of rostering problems that we can 'model and run'.
A constructive proof of the general Lovasz Local Lemma
Venue: arXiv cs.DS 2009
Year: 2009

The Lovasz Local Lemma [EL75] is a powerful tool to non-constructively prove the existence of combinatorial objects meeting a prescribed collection of criteria. In his breakthrough paper [Bec91], Beck demonstrated that a constructive variant can be given under certain more restrictive conditions. Simplifications of his procedure and relaxations of its restrictions were subsequently exhibited in several publications [Alo91, MR98, CS00, Mos06, Sri08, Mos08]. In [Mos09], a constructive proof was presented that works under negligible restrictions, formulated in terms of the Bounded Occurrence Satisfiability problem. In the present paper, we reformulate and improve upon these findings so as to directly apply to almost all known applications of the general Local Lemma.
Expert System for Quality Assessment in "Tibiscus" University
Venue: arXiv cs.CY 2009
Year: 2009

The periodical evaluation of the teaching staff in "Tibiscus" University is based on the specification of the Romanian Agency for Quality Assurance in Higher Education (ARACIS), namely "The quality of teaching and researching staff: The universities must dispose of teaching staff which, as number and functional base must be correctly allocated to the total number of students, depending on the study domain and regarding the qualifications it must depend on the specific of the study program and the proposed quality objectives." This paper presents the implementation of an expert system, offering to the students the possibility to perform the evaluation in a modern way and to the evaluation committee a quick access to all necessary data.
Achievable Sum Rate of MIMO MMSE Recievers: A General Analytic Framework
Venue: arXiv cs.IT 2009
Year: 2009

This paper investigates the achievable sum rate of multiple-input multiple-output (MIMO) wireless systems employing linear minimum mean-squared error (MMSE) receivers. We present a new analytic framework which unveils an interesting connection between the achievable sum rate with MMSE receivers and the ergodic mutual information achieved with optimal receivers. This simple but powerful result enables the vast prior literature on ergodic MIMO mutual information to be directly applied to the analysis of MMSE receivers. The framework is particularized to various Rayleigh and Rician channel scenarios to yield new exact closed-form expressions for the achievable sum rate, as well as simplified expressions in the asymptotic regimes of high and low signal to noise ratios. These expressions lead to the discovery of key insights into the performance of MIMO MMSE receivers under practical channel conditions.
Linear-time nearest point algorithms for Coxeter lattices
Venue: arXiv cs.IT 2009
Year: 2009

The Coxeter lattices, which we denote $A_{n/m}$, are a family of lattices containing many of the important lattices in low dimensions. This includes $A_n$, $E_7$, $E_8$ and their duals $A_n^*$, $E_7^*$ and $E_8^*$. We consider the problem of finding a nearest point in a Coxeter lattice. We describe two new algorithms, one with worst case arithmetic complexity $O(n\log{n})$ and the other with worst case complexity O(n) where $n$ is the dimension of the lattice. We show that for the particular lattices $A_n$ and $A_n^*$ the algorithms reduce to simple nearest point algorithms that already exist in the literature.
Preserving Individual Privacy in Serial Data Publishing
Venue: arXiv cs.DB 2009
Year: 2009

While previous works on privacy-preserving serial data publishing consider the scenario where sensitive values may persist over multiple data releases, we find that no previous work has sufficient protection provided for sensitive values that can change over time, which should be the more common case. In this work we propose to study the privacy guarantee for such transient sensitive values, which we call the global guarantee. We formally define the problem for achieving this guarantee and derive some theoretical properties for this problem. We show that the anonymized group sizes used in the data anonymization is a key factor in protecting individual privacy in serial publication. We propose two strategies for anonymization targeting at minimizing the average group size and the maximum group size. Finally, we conduct experiments on a medical dataset to show that our method is highly efficient and also produces published data of very high utility.
Digital Ecosystems in the Clouds: Towards Community Cloud Computing
Venue: arXiv cs.NI 2009
Year: 2009

Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns of privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon, and Microsoft. Community Cloud Computing makes use of the principles of Digital Ecosystems to provide a paradigm for Clouds in the community, offering an alternative architecture for the use cases of Cloud Computing. It is more technically challenging to deal with issues of distributed computing, such as latency, differential resource management, and additional security requirements. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.
Grid Technologies
Venue: arXiv cs.DC 2009
Year: 2009

This paper contains the most important aspects of computing grids. Grid computing allows high performance distributed systems to act as a single computer. An overview of grids structure and techniques is given in order to understand the way grids work.
C# - Connecting a Mobile Application to Oracle Server via Web Services
Venue: arXiv cs.NI 2009
Year: 2009

This article is focused on mobile development using Visual Studio 2005, web services and their connection to Oracle server, willing to help programmers to realize simple and useful mobile applications.
An Epistemic Approach to Coercion-Resistance for Electronic Voting Protocols
Venue: arXiv cs.CR 2009
Year: 2009

Coercion resistance is an important and one of the most intricate security requirements of electronic voting protocols. Several definitions of coercion resistance have been proposed in the literature, including definitions based on symbolic models. However, existing definitions in such models are rather restricted in their scope and quite complex. In this paper, we therefore propose a new definition of coercion resistance in a symbolic setting, based on an epistemic approach. Our definition is relatively simple and intuitive. It allows for a fine-grained formulation of coercion resistance and can be stated independently of a specific, symbolic protocol and adversary model. As a proof of concept, we apply our definition to three voting protocols. In particular, we carry out the first rigorous analysis of the recently proposed Civitas system. We precisely identify those conditions under which this system guarantees coercion resistance or fails to be coercion resistant. We also analyze protocols proposed by Lee et al. and Okamoto.
Directing RF Terminals Using TELNET Applications
Venue: arXiv cs.OH 2009
Year: 2009

The present study aims to emphasize the way in which the TELNET protocol for directing the mobile terminals is used and works. The paper is structured in three parts: the first two parts are a theoretic presentation of the TELNET protocol, respectively of the mobile terminals. The third part contains an application of the way in which a mobile terminal can be programmed using the TELNET protocol.