OpenRaiser/Intern-Atlas huggingface dataset:
Learning invariant features through local space contraction
Venue: arXiv cs.AI 2011
Year: 2011

We present in this paper a novel approach for training deterministic auto-encoders. We show that by adding a well chosen penalty term to the classical reconstruction cost function, we can achieve results that equal or surpass those attained by other regularized auto-encoders as well as denoising auto-encoders on a range of datasets. This penalty term corresponds to the Frobenius norm of the Jacobian matrix of the encoder activations with respect to the input. We show that this penalty term results in a localized space contraction which in turn yields robust features on the activation layer. Furthermore, we show how this penalty term is related to both regularized auto-encoders and denoising encoders and how it can be seen as a link between deterministic and non-deterministic auto-encoders. We find empirically that this penalty helps to carve a representation that better captures the local directions of variation dictated by the data, corresponding to a lower-dimensional non-linear manifold, while being more invariant to the vast majority of directions orthogonal to the manifold. Finally, we show that by using the learned features to initialize a MLP, we achieve state of the art classification error on a range of datasets, surpassing other methods of pre-training.
Interference Mitigation for Cognitive Radio MIMO Systems Based on Practical Precoding
Venue: arXiv cs.IT 2011
Year: 2011

In this paper, we propose two subspace-projection-based precoding schemes, namely, full-projection (FP)- and partial-projection (PP)-based precoding, for a cognitive radio multiple-input multiple-output (CR-MIMO) network to mitigate its interference to a primary time-division-duplexing (TDD) system. The proposed precoding schemes are capable of estimating interference channels between CR and primary networks, and incorporating the interference from the primary to the CR system into CR precoding via a novel sensing approach. Then, the CR performance and resulting interference of the proposed precoding schemes are analyzed and evaluated. By fully projecting the CR transmission onto a null space of the interference channels, the FP-based precoding scheme can effectively avoid interfering the primary system with boosted CR throughput. While, the PP-based scheme is able to further improve the CR throughput by partially projecting its transmission onto the null space.
New parameterized algorithms for edge dominating set
Venue: arXiv cs.DM 2011
Year: 2011

An edge dominating set of a graph G=(V,E) is a subset M of edges in the graph such that each edge in E-M is incident with at least one edge in M. In an instance of the parameterized edge dominating set problem we are given a graph G=(V,E) and an integer k and we are asked to decide whether G has an edge dominating set of size at most k. In this paper we show that the parameterized edge dominating set problem can be solved in O^*(2.3147^k) time and polynomial space. We show that this problem can be reduced to a quadratic kernel with O(k^3) edges.
Rank Minimization over Finite Fields: Fundamental Limits and Coding-Theoretic Interpretations
Venue: arXiv cs.IT 2011
Year: 2011

This paper establishes information-theoretic limits in estimating a finite field low-rank matrix given random linear measurements of it. These linear measurements are obtained by taking inner products of the low-rank matrix with random sensing matrices. Necessary and sufficient conditions on the number of measurements required are provided. It is shown that these conditions are sharp and the minimum-rank decoder is asymptotically optimal. The reliability function of this decoder is also derived by appealing to de Caen's lower bound on the probability of a union. The sufficient condition also holds when the sensing matrices are sparse - a scenario that may be amenable to efficient decoding. More precisely, it is shown that if the n\times n-sensing matrices contain, on average, Ω(nlog n) entries, the number of measurements required is the same as that when the sensing matrices are dense and contain entries drawn uniformly at random from the field. Analogies are drawn between the above results and rank-metric codes in the coding theory literature. In fact, we are also strongly motivated by understanding when minimum rank distance decoding of random rank-metric codes succeeds. To this end, we derive distance properties of equiprobable and sparse rank-metric codes. These distance properties provide a precise geometric interpretation of the fact that the sparse ensemble requires as few measurements as the dense one. Finally, we provide a non-exhaustive procedure to search for the unknown low-rank matrix.
Relativistic virtual worlds: an emerging framework
Venue: arXiv cs.HC 2011
Year: 2011

In this paper, I will attempt to establish a framework for representation in virtual worlds that may allow for input data from many different scales and virtual physics to be merged. For example, a typical virtual environment must effectively handle user input, sensor data, and virtual world physics all in real- time. Merging all of these data into a single interactive system requires that we adapt approaches from topological methods such as n-dimensional relativistic representation. A number of hypothetical examples will be provided throughout the paper to clarify technical challenges that need to be overcome to realize this vision. The long-term goal of this work is that truly invariant representations will ultimately result from establishing formal, inclusive relationships between these different domains. Using this framework, incomplete information in one or more domains can be compensated for by parallelism and mappings within the virtual world representation. To introduce this approach, I will review recent developments in embodiment, virtual world technology, and neuroscience relevant to the control of virtual worlds. The next step will be to borrow ideas from fields such as brain science, applied mathematics, and cosmology to give proper perspective to this approach. A simple demonstration will then be given using an intuitive example of physical relativism. Finally, future directions for the application of this method will be considered.
On Using Seeders for P2P Live Streaming
Venue: arXiv cs.NI 2011
Year: 2011

Seeders (peers that do not request anything but contribute to the system) are a powerful concept in peer-to-peer (P2P). They allow to leverage the capacities of a P2P system. While seeding is a natural idea for filesharing or video-on-demand applications, it seems somehow counter-intuitive in the context of live streaming. This paper aims at describing the feasibility and performance of P2P live seeding. After a formal definition of "live seeding" and efficiency, we consider the theoretical performance of systems where the overhead is neglected. We then propose a linear overhead model and extend the results for this model, for a single seeder and for a set of seeders as well (it is not always possible to perfectly aggregate individual efficiencies in a given system).
A Machine Learning Based Analytical Framework for Semantic Annotation Requirements
Venue: arXiv cs.AI 2011
Year: 2011

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as multilinguality, scalability, and issues which are related to diversity and inconsistency in content of different web pages. Due to the wide range of domains and the dynamic environments that the Semantic Annotation systems must be performed on, the problem of automating annotation process is one of the significant challenges in this domain. To overcome this problem, different machine learning approaches such as supervised learning, unsupervised learning and more recent ones like, semi-supervised learning and active learning have been utilized. In this paper we present an inclusive layered classification of Semantic Annotation challenges and discuss the most important issues in this field. Also, we review and analyze machine learning applications for solving semantic annotation problems. For this goal, the article tries to closely study and categorize related researches for better understanding and to reach a framework that can map machine learning techniques into the Semantic Annotation challenges and requirements.
Combining Ontology Development Methodologies and Semantic Web Platforms for E-government Domain Ontology Development
Venue: arXiv cs.AI 2011
Year: 2011

One of the key challenges in electronic government (e-government) is the development of systems that can be easily integrated and interoperated to provide seamless services delivery to citizens. In recent years, Semantic Web technologies based on ontology have emerged as promising solutions to the above engineering problems. However, current research practicing semantic development in e-government does not focus on the application of available methodologies and platforms for developing government domain ontologies. Furthermore, only a few of these researches provide detailed guidelines for developing semantic ontology models from a government service domain. This research presents a case study combining an ontology building methodology and two state-of-the-art Semantic Web platforms namely Protege and Java Jena ontology API for semantic ontology development in e-government. Firstly, a framework adopted from the Uschold and King ontology building methodology is employed to build a domain ontology describing the semantic content of a government service domain. Thereafter, UML is used to semi-formally represent the domain ontology. Finally, Protege and Jena API are employed to create the Web Ontology Language (OWL) and Resource Description Framework (RDF) representations of the domain ontology respectively to enable its computer processing. The study aims at: (1) providing e-government developers, particularly those from the developing world with detailed guidelines for practicing semantic content development in their e-government projects and (2), strengthening the adoption of semantic technologies in e-government. The study would also be of interest to novice Semantic Web developers who might used it as a starting point for further investigations.
Arc Consistency and Friends
Venue: arXiv cs.AI 2011
Year: 2011

A natural and established way to restrict the constraint satisfaction problem is to fix the relations that can be used to pose constraints; such a family of relations is called a constraint language. In this article, we study arc consistency, a heavily investigated inference method, and three extensions thereof from the perspective of constraint languages. We conduct a comparison of the studied methods on the basis of which constraint languages they solve, and we present new polynomial-time tractability results for singleton arc consistency, the most powerful method studied.
High Degree Vertices, Eigenvalues and Diameter of Random Apollonian Networks
Venue: arXiv cs.SI 2011
Year: 2011

In this work we analyze basic properties of Random Apollonian Networks \cite{zhang,zhou}, a popular stochastic model which generates planar graphs with power law properties. Specifically, let $k$ be a constant and $Δ_1 \geq Δ_2 \geq .. \geq Δ_k$ be the degrees of the $k$ highest degree vertices. We prove that at time $t$, for any function $f$ with $f(t) \rightarrow +\infty$ as $t \rightarrow +\infty$, $\frac{t^{1/2}}{f(t)} \leq Δ_1 \leq f(t)t^{1/2}$ and for $i=2,...,k=O(1)$, $\frac{t^{1/2}}{f(t)} \leq Δ_i \leq Δ_{i-1} - \frac{t^{1/2}}{f(t)}$ with high probability (\whp). Then, we show that the $k$ largest eigenvalues of the adjacency matrix of this graph satisfy $λ_k = (1\pm o(1))Δ_k^{1/2}$ \whp. Furthermore, we prove a refined upper bound on the asymptotic growth of the diameter, i.e., that \whp the diameter $d(G_t)$ at time $t$ satisfies $d(G_t) \leq ρ\log{t}$ where $\frac{1}ρ=η$ is the unique solution greater than 1 of the equation $η- 1 - \logη = \log{3}$. Finally, we investigate other properties of the model.
Xampling in Ultrasound Imaging
Venue: arXiv cs.IT 2011
Year: 2011

Recent developments of new medical treatment techniques put challenging demands on ultrasound imaging systems in terms of both image quality and raw data size. Traditional sampling methods result in very large amounts of data, thus, increasing demands on processing hardware and limiting the exibility in the post-processing stages. In this paper, we apply Compressed Sensing (CS) techniques to analog ultrasound signals, following the recently developed Xampling framework. The result is a system with significantly reduced sampling rates which, in turn, means significantly reduced data size while maintaining the quality of the resulting images.
Model based system engineering approach of a lightweight embedded TCP/IP
Venue: arXiv cs.SE 2011
Year: 2011

The use of embedded software is growing very rapidly. Accessing the internet is a necessary service which has large range of applications in many fields. The Internet is based on TCP/IP which is a very important stack. Although TCP/IP is very important there is not a software engineering model describing it. The common method in modeling and describing TCP/IP is RFCs which is not sufficient for software engineer and developers. Therefore there is a need for software engineering approach to help engineers and developers to customize their own web based applications for embedded systems. This research presents a model based system engineering approach of lightweight TCP/IP. The model contains the necessary phases for developing a lightweight TCP/IP for embedded systems. The proposed model is based on SysML as a model based system engineering language.
On Optimality of Greedy Policy for a Class of Standard Reward Function of Restless Multi-armed Bandit Problem
Venue: arXiv cs.LG 2011
Year: 2011

In this paper,we consider the restless bandit problem, which is one of the most well-studied generalizations of the celebrated stochastic multi-armed bandit problem in decision theory. However, it is known be PSPACE-Hard to approximate to any non-trivial factor. Thus the optimality is very difficult to obtain due to its high complexity. A natural method is to obtain the greedy policy considering its stability and simplicity. However, the greedy policy will result in the optimality loss for its intrinsic myopic behavior generally. In this paper, by analyzing one class of so-called standard reward function, we establish the closed-form condition about the discounted factor βsuch that the optimality of the greedy policy is guaranteed under the discounted expected reward criterion, especially, the condition β= 1 indicating the optimality of the greedy policy under the average accumulative reward criterion. Thus, the standard form of reward function can easily be used to judge the optimality of the greedy policy without any complicated calculation. Some examples in cognitive radio networks are presented to verify the effectiveness of the mathematical result in judging the optimality of the greedy policy.
QoS Provisioning for Multimedia Transmission in Cognitive Radio Networks
Venue: arXiv cs.IT 2011
Year: 2011

In cognitive radio (CR) networks, the perceived reduction of application layer quality of service (QoS), such as multimedia distortion, by secondary users may impede the success of CR technologies. Most previous work in CR networks ignores application layer QoS. In this paper we take an integrated design approach to jointly optimize multimedia intra refreshing rate, an application layer parameter, together with access strategy, and spectrum sensing for multimedia transmission in a CR system with time varying wireless channels. Primary network usage and channel gain are modeled as a finite state Markov process. With channel sensing and channel state information errors, the system state cannot be directly observed. We formulate the QoS optimization problem as a partially observable Markov decision process (POMDP). A low complexity dynamic programming framework is presented to obtain the optimal policy. Simulation results show the effectiveness of the proposed scheme.
Consistent Labeling of Rotating Maps
Venue: arXiv cs.CG 2011
Year: 2011

Dynamic maps that allow continuous map rotations, e.g., on mobile devices, encounter new issues unseen in static map labeling before. We study the following dynamic map labeling problem: The input is a static, labeled map, i.e., a set P of points in the plane with attached non-overlapping horizontal rectangular labels. The goal is to find a consistent labeling of P under rotation that maximizes the number of visible labels for all rotation angles such that the labels remain horizontal while the map is rotated. A labeling is consistent if a single active interval of angles is selected for each label such that labels neither intersect each other nor occlude points in P at any rotation angle. We first introduce a general model for labeling rotating maps and derive basic geometric properties of consistent solutions. We show NP-completeness of the active interval maximization problem even for unit-square labels. We then present a constant-factor approximation for this problem based on line stabbing, and refine it further into an efficient polynomial-time approximation scheme (EPTAS). Finally, we extend the EPTAS to the more general setting of rectangular labels of bounded size and aspect ratio.
On the Impact of Fair Best Response Dynamics
Venue: arXiv cs.GT 2011
Year: 2011

In this work we completely characterize how the frequency with which each player participates in the game dynamics affects the possibility of reaching efficient states, i.e., states with an approximation ratio within a constant factor from the price of anarchy, within a polynomially bounded number of best responses. We focus on the well known class of congestion games and we show that, if each player is allowed to play at least once and at most $β$ times any $T$ best responses, states with approximation ratio $O(β)$ times the price of anarchy are reached after $T \lceil \log \log n \rceil$ best responses, and that such a bound is essentially tight also after exponentially many ones. One important consequence of our result is that the fairness among players is a necessary and sufficient condition for guaranteeing a fast convergence to efficient states. This answers the important question of the maximum order of $β$ needed to fast obtain efficient states, left open by [9,10] and [3], in which fast convergence for constant $β$ and very slow convergence for $β=O(n)$ have been shown, respectively. Finally, we show that the structure of the game implicitly affects its performances. In particular, we show that in the symmetric setting, in which all players share the same set of strategies, the game always converges to an efficient state after a polynomial number of best responses, regardless of the frequency each player moves with.
Asynchronous mobile robot gathering from symmetric configurations without global multiplicity detection
Venue: arXiv cs.DC 2011
Year: 2011

We consider a set of k autonomous robots that are endowed with visibility sensors (but that are otherwise unable to communicate) and motion actuators. Those robots must collaborate to reach a sin- gle vertex that is unknown beforehand, and to remain there hereafter. Previous works on gathering in ring-shaped networks suggest that there exists a tradeoff between the size of the set of potential initial configurations, and the power of the sensing capabilities of the robots (i.e. the larger the initial configuration set, the most powerful the sensor needs to be). We prove that there is no such trade off. We propose a gathering protocol for an odd number of robots in a ring-shaped network that allows symmetric but not periodic configurations as initial configurations, yet uses only local weak multiplicity detection. Robots are assumed to be anonymous and oblivious, and the execution model is the non-atomic CORDA model with asynchronous fair scheduling. Our protocol allows the largest set of initial configurations (with respect to impossibility results) yet uses the weakest multiplicity detector to date. The time complexity of our protocol is O(n2), where n denotes the size of the ring. Compared to previous work that also uses local weak multiplicity detection, we do not have the constraint that k < n/2 (here, we simply have 2 < k < n - 3).
Survey of Cognitive Radio Techniques in Wireless Network
Venue: arXiv cs.MM 2011
Year: 2011

In this report, I surveyed the cognitive radio technique in wireless networks. Researched several kinds of cognitive techniques about their advantages and disadvantages.
Access Control Mechanisms for Semantic Web services-A Discussion on Requirements & Future Directions
Venue: arXiv cs.OH 2011
Year: 2011

Semantic Web is an open, distributed, and dynamic environment where access to resources cannot be controlled in a safe manner unless the access decision takes into account during discovery of web services. Security becomes the crucial factor for the adoption of the semantic based web services. An access control means that the users must fulfill certain conditions in order to gain access over web services. Access control is important in both perspectives i.e. legal and security point of view. This paper discusses important requirements for effective access control in semantic web services which have been extracted from the literature surveyed. I have also discussed open research issues in this context, focusing on access control policies and models in this paper.
Quantum counter automata
Venue: arXiv cs.CC 2011
Year: 2011

The question of whether quantum real-time one-counter automata (rtQ1CAs) can outperform their probabilistic counterparts has been open for more than a decade. We provide an affirmative answer to this question, by demonstrating a non-context-free language that can be recognized with perfect soundness by a rtQ1CA. This is the first demonstration of the superiority of a quantum model to the corresponding classical one in the real-time case with an error bound less than 1. We also introduce a generalization of the rtQ1CA, the quantum one-way one-counter automaton (1Q1CA), and show that they too are superior to the corresponding family of probabilistic machines. For this purpose, we provide general definitions of these models that reflect the modern approach to the definition of quantum finite automata, and point out some problems with previous results. We identify several remaining open problems.
Derandomization of Online Assignment Algorithms for Dynamic Graphs
Venue: arXiv cs.CC 2011
Year: 2011

This paper analyzes different online algorithms for the problem of assigning weights to edges in a fully-connected bipartite graph that minimizes the overall cost while satisfying constraints. Edges in this graph may disappear and reappear over time. Performance of these algorithms is measured using simulations. This paper also attempts to derandomize the randomized online algorithm for this problem.
A Formal Model of Anonymous Systems
Venue: arXiv cs.DC 2011
Year: 2011

We put forward a formal model of anonymous systems. And we concentrate on the anonymous failure detectors in our model. In particular, we give three examples of anonymous failure detectors and show that they can be used to solve the consensus problem and that they are equivalent to their classic counterparts. Moreover, we show some relationship among them and provide a simple classification of anonymous failure detectors.