OpenRaiser/Intern-Atlas huggingface dataset:
Learning Random Kernel Approximations for Object Recognition
Venue: arXiv cs.CV 2012
Year: 2012

Approximations based on random Fourier features have recently emerged as an efficient and formally consistent methodology to design large-scale kernel machines. By expressing the kernel as a Fourier expansion, features are generated based on a finite set of random basis projections, sampled from the Fourier transform of the kernel, with inner products that are Monte Carlo approximations of the original kernel. Based on the observation that different kernel-induced Fourier sampling distributions correspond to different kernel parameters, we show that an optimization process in the Fourier domain can be used to identify the different frequency bands that are useful for prediction on training data. Moreover, the application of group Lasso to random feature vectors corresponding to a linear combination of multiple kernels, leads to efficient and scalable reformulations of the standard multiple kernel learning model \cite{Varma09}. In this paper we develop the linear Fourier approximation methodology for both single and multiple gradient-based kernel learning and show that it produces fast and accurate predictors on a complex dataset such as the Visual Object Challenge 2011 (VOC2011).
Tree Regular Model Checking for Lattice-Based Automata
Venue: arXiv cs.FL 2012
Year: 2012

Tree Regular Model Checking (TRMC) is the name of a family of techniques for analyzing infinite-state systems in which states are represented by terms, and sets of states by Tree Automata (TA). The central problem in TRMC is to decide whether a set of bad states is reachable. The problem of computing a TA representing (an over- approximation of) the set of reachable states is undecidable, but efficient solutions based on completion or iteration of tree transducers exist. Unfortunately, the TRMC framework is unable to efficiently capture both the complex structure of a system and of some of its features. As an example, for JAVA programs, the structure of a term is mainly exploited to capture the structure of a state of the system. On the counter part, integers of the java programs have to be encoded with Peano numbers, which means that any algebraic operation is potentially represented by thousands of applications of rewriting rules. In this paper, we propose Lattice Tree Automata (LTAs), an extended version of tree automata whose leaves are equipped with lattices. LTAs allow us to represent possibly infinite sets of interpreted terms. Such terms are capable to represent complex domains and related operations in an efficient manner. We also extend classical Boolean operations to LTAs. Finally, as a major contribution, we introduce a new completion-based algorithm for computing the possibly infinite set of reachable interpreted terms in a finite amount of time.
Invariant Scattering Convolution Networks
Venue: arXiv cs.CV 2012
Year: 2012

A wavelet scattering network computes a translation invariant image representation, which is stable to deformations and preserves high frequency information for classification. It cascades wavelet transform convolutions with non-linear modulus and averaging operators. The first network layer outputs SIFT-type descriptors whereas the next layers provide complementary invariant information which improves classification. The mathematical analysis of wavelet scattering networks explains important properties of deep convolution networks for classification. A scattering representation of stationary processes incorporates higher order moments and can thus discriminate textures having the same Fourier power spectrum. State of the art classification results are obtained for handwritten digits and texture discrimination, using a Gaussian kernel SVM and a generative PCA classifier.
Optimum Subcodes of Self-Dual Codes and Their Optimum Distance Profiles
Venue: arXiv cs.IT 2012
Year: 2012

Binary optimal codes often contain optimal or near-optimal subcodes. In this paper we show that this is true for the family of self-dual codes. One approach is to compute the optimum distance profiles (ODPs) of linear codes, which was introduced by Luo, et. al. (2010). One of our main results is the development of general algorithms, called the Chain Algorithms, for finding ODPs of linear codes. Then we determine the ODPs for the Type II codes of lengths up to 24 and the extremal Type II codes of length 32, give a partial result of the ODP of the extended quadratic residue code $q_{48}$ of length 48. We also show that there does not exist a $[48,k,16]$ subcode of $q_{48}$ for $k \ge 17$, and we find a first example of a doubly-even self-complementary $[48, 16, 16]$ code.
A Two-Dimensional Signal Space for Intensity-Modulated Channels
Venue: arXiv cs.IT 2012
Year: 2012

A two-dimensional signal space for intensity- modulated channels is presented. Modulation formats using this signal space are designed to maximize the minimum distance between signal points while satisfying average and peak power constraints. The uncoded, high-signal-to-noise ratio, power and spectral efficiencies are compared to those of the best known formats. The new formats are simpler than existing subcarrier formats, and are superior if the bandwidth is measured as 90% in-band power. Existing subcarrier formats are better if the bandwidth is measured as 99% in-band power.
Programming with Algebraic Effects and Handlers
Venue: arXiv cs.PL 2012
Year: 2012

Eff is a programming language based on the algebraic approach to computational effects, in which effects are viewed as algebraic operations and effect handlers as homomorphisms from free algebras. Eff supports first-class effects and handlers through which we may easily define new computational effects, seamlessly combine existing ones, and handle them in novel ways. We give a denotational semantics of eff and discuss a prototype implementation based on it. Through examples we demonstrate how the standard effects are treated in eff, and how eff supports programming techniques that use various forms of delimited continuations, such as backtracking, breadth-first search, selection functionals, cooperative multi-threading, and others.
BotMosaic: Collaborative Network Watermark for Botnet Detection
Venue: arXiv cs.CR 2012
Year: 2012

Recent research has made great strides in the field of detecting botnets. However, botnets of all kinds continue to plague the Internet, as many ISPs and organizations do not deploy these techniques. We aim to mitigate this state by creating a very low-cost method of detecting infected bot host. Our approach is to leverage the botnet detection work carried out by some organizations to easily locate collaborating bots elsewhere. We created BotMosaic as a countermeasure to IRC-based botnets. BotMosaic relies on captured bot instances controlled by a watermarker, who inserts a particular pattern into their network traffic. This pattern can then be detected at a very low cost by client organizations and the watermark can be tuned to provide acceptable false-positive rates. A novel feature of the watermark is that it is inserted collaboratively into the flows of multiple captured bots at once, in order to ensure the signal is strong enough to be detected. BotMosaic can also be used to detect stepping stones and to help trace back to the botmaster. It is content agnostic and can operate on encrypted traffic. We evaluate BotMosaic using simulations and a testbed deployment.
Known algorithms for EDGE CLIQUE COVER are probably optimal
Venue: arXiv cs.DS 2012
Year: 2012

In the EDGE CLIQUE COVER (ECC) problem, given a graph G and an integer k, we ask whether the edges of G can be covered with k complete subgraphs of G or, equivalently, whether G admits an intersection model on k-element universe. Gramm et al. [JEA 2008] have shown a set of simple rules that reduce the number of vertices of G to 2^k, and no algorithm is known with significantly better running time bound than a brute-force search on this reduced instance. In this paper we show that the approach of Gramm et al. is essentially optimal: we present a polynomial time algorithm that reduces an arbitrary 3-CNF-SAT formula with n variables and m clauses to an equivalent ECC instance (G,k) with k = O(log n) and |V(G)| = O(n + m). Consequently, there is no 2^{2^{o(k)}}poly(n) time algorithm for the ECC problem, unless the Exponential Time Hypothesis fails. To the best of our knowledge, these are the first results for a natural, fixed-parameter tractable problem, and proving that a doubly-exponential dependency on the parameter is essentially necessary.
Coordinated Beamforming with Relaxed Zero Forcing: The Sequential Orthogonal Projection Combining Method and Rate Control
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, coordinated beamforming based on relaxed zero forcing (RZF) for K transmitter-receiver pair multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) interference channels is considered. In the RZF coordinated beamforming, conventional zero-forcing interference leakage constraints are relaxed so that some predetermined interference leakage to undesired receivers is allowed in order to increase the beam design space for larger rates than those of the zero-forcing (ZF) scheme or to make beam design feasible when ZF is impossible. In the MISO case, it is shown that the rate-maximizing beam vector under the RZF framework for a given set of interference leakage levels can be obtained by sequential orthogonal projection combining (SOPC). Based on this, exact and approximate closed-form solutions are provided in two-user and three-user cases, respectively, and an efficient beam design algorithm for RZF coordinated beamforming is provided in general cases. Furthermore, the rate control problem under the RZF framework is considered. A centralized approach and a distributed heuristic approach are proposed to control the position of the designed rate-tuple in the achievable rate region. Finally, the RZF framework is extended to MIMO interference channels by deriving a new lower bound on the rate of each user.
Thermal analysis & optimization of a 3 dimensional heterogeneous structure
Venue: arXiv cs.ET 2012
Year: 2012

Besides the lot of advantages offered by the 3D stacking of devices in an integrated circuit there is a chance of device damage due to rise in peak temperature value. Hence, in order to make use of all the potential benefits of the vertical stacking a thermal aware design is very essential. The first step for designing a thermal aware architecture is to analyze the hotspot temperature generated by the devices. In this paper we are presenting the results of our thermal analysis experiments of a 3D heterogeneous structure with three layers. The bottom layer had eight identical processors at 2.4 GHz and the top layer was with four memory units. The intermediate layer was a thermal interface material (TIM). The 2D thermal analysis of the top and bottom layers was also done separately. In the next step simulations were carried out by varying TIM thickness and conductivity to study its affect on hotspot temperature so as to optimize the temperature distribution.
Near-Optimal Compressive Binary Search
Venue: arXiv cs.IT 2012
Year: 2012

We propose a simple modification to the recently proposed compressive binary search. The modification removes an unnecessary and suboptimal factor of log log n from the SNR requirement, making the procedure optimal (up to a small constant). Simulations show that the new procedure performs significantly better in practice as well. We also contrast this problem with the more well known problem of noisy binary search.
Matrix Representation of Iterative Approximate Byzantine Consensus in Directed Graphs
Venue: arXiv cs.DC 2012
Year: 2012

This paper presents a proof of correctness of an iterative approximate Byzantine consensus (IABC) algorithm for directed graphs. The iterative algorithm allows fault- free nodes to reach approximate conensus despite the presence of up to f Byzantine faults. Necessary conditions on the underlying network graph for the existence of a correct IABC algorithm were shown in our recent work [15, 16]. [15] also analyzed a specific IABC algorithm and showed that it performs correctly in any network graph that satisfies the necessary condition, proving that the necessary condition is also sufficient. In this paper, we present an alternate proof of correctness of the IABC algorithm, using a familiar technique based on transition matrices [9, 3, 17, 19]. The key contribution of this paper is to exploit the following observation: for a given evolution of the state vector corresponding to the state of the fault-free nodes, many alternate state transition matrices may be chosen to model that evolution cor- rectly. For a given state evolution, we identify one approach to suitably "design" the transition matrices so that the standard tools for proving convergence can be applied to the Byzantine fault-tolerant algorithm as well. In particular, the transition matrix for each iteration is designed such that each row of the matrix contains a large enough number of elements that are bounded away from 0.
Distributional Measures as Proxies for Semantic Relatedness
Venue: arXiv cs.CL 2012
Year: 2012

The automatic ranking of word pairs as per their semantic relatedness and ability to mimic human notions of semantic relatedness has widespread applications. Measures that rely on raw data (distributional measures) and those that use knowledge-rich ontologies both exist. Although extensive studies have been performed to compare ontological measures with human judgment, the distributional measures have primarily been evaluated by indirect means. This paper is a detailed study of some of the major distributional measures; it lists their respective merits and limitations. New measures that overcome these drawbacks, that are more in line with the human notions of semantic relatedness, are suggested. The paper concludes with an exhaustive comparison of the distributional and ontology-based measures. Along the way, significant research problems are identified. Work on these problems may lead to a better understanding of how semantic relatedness is to be measured.
Effective M-learning design Strategies for computer science and Engineering courses
Venue: arXiv cs.HC 2012
Year: 2012

Mobile learning (M-learning) is receiving more attention as a method of delivering to learners study materials anytime and anywhere. It is a necessity for educators to come up with a layout for learning that can be accessed through mobile devices. These learning materials should consist of good quality learning theories and accurate instructional layout in order to maintain the learning as effective as possible. It is important to follow certain strategies that can help the developers for M-learning applications. In this paper we proposed a set of strategies that are useful for creating mobile prototype for Computer Science and Engineering courses or M-learning application for course content.
Icebergs in the Clouds: the Other Risks of Cloud Computing
Venue: arXiv cs.CY 2012
Year: 2012

Cloud computing is appealing from management and efficiency perspectives, but brings risks both known and unknown. Well-known and hotly-debated information security risks, due to software vulnerabilities, insider attacks, and side-channels for example, may be only the "tip of the iceberg." As diverse, independently developed cloud services share ever more fluidly and aggressively multiplexed hardware resource pools, unpredictable interactions between load-balancing and other reactive mechanisms could lead to dynamic instabilities or "meltdowns." Non-transparent layering structures, where alternative cloud services may appear independent but share deep, hidden resource dependencies, may create unexpected and potentially catastrophic failure correlations, reminiscent of financial industry crashes. Finally, cloud computing exacerbates already-difficult digital preservation challenges, because only the provider of a cloud-based application or service can archive a "live," functional copy of a cloud artifact and its data for long-term cultural preservation. This paper explores these largely unrecognized risks, making the case that we should study them before our socioeconomic fabric becomes inextricably dependent on a convenient but potentially unstable computing model.
On the Effect of Channel Fading on Greedy Scheduling
Venue: arXiv cs.NI 2012
Year: 2012

Greedy Maximal Scheduling (GMS) is an attractive low-complexity scheme for scheduling in wireless networks. Recent work has characterized its throughput for the case when there is no fading/channel variations. This paper aims to understand the effect of channel variations on the relative throughput performance of GMS vis-a-vis that of an optimal scheduler facing the same fading. The effect is not a-priori obvious because, on the one hand, fading could help by decoupling/precluding global states that lead to poor GMS performance, while on the other hand fading adds another degree of freedom in which an event unfavourable to GMS could occur. We show that both these situations can occur when fading is adversarial. In particular, we first define the notion of a {\em Fading Local Pooling factor (F-LPF)}, and show that it exactly characterizes the throughput of GMS in this setting. We also derive general upper and lower bounds on F-LPF. Using these bounds, we provide two example networks - one where the relative performance of GMS is worse than if there were no fading, and one where it is better.
Towards MAC/Anycast Diversity in IEEE 802.11n MIMO Networks
Venue: arXiv cs.NI 2012
Year: 2012

Opportunistic Routing (OR) is a novel routing technique for wireless mesh networks that exploits the broadcast nature of the wireless medium. OR combines frames from multiple receivers and therefore creates a form of Spatial Diversity, called MAC Diversity. The gain from OR is especially high in networks where the majority of links has a high packet loss probability. The updated IEEE 802.11n standard improves the physical layer with the ability to use multiple transmit and receive antennas, i.e. Multiple-Input and Multiple-Output (MIMO), and therefore already offers spatial diversity on the physical layer, i.e. called Physical Diversity, which improves the reliability of a wireless link by reducing its error rate. In this paper we quantify the gain from MAC diversity as utilized by OR in the presence of PHY diversity as provided by a MIMO system like 802.11n. We experimented with an IEEE 802.11n indoor testbed and analyzed the nature of packet losses. Our experiment results show negligible MAC diversity gains for both interference-prone 2.4 GHz and interference-free 5 GHz channels when using 802.11n. This is different to the observations made with single antenna systems based on 802.11b/g, as well as in initial studies with 802.11n.
Tiresias: Online Anomaly Detection for Hierarchical Operational Network Data
Venue: arXiv cs.NI 2012
Year: 2012

Operational network data, management data such as customer care call logs and equipment system logs, is a very important source of information for network operators to detect problems in their networks. Unfortunately, there is lack of efficient tools to automatically track and detect anomalous events on operational data, causing ISP operators to rely on manual inspection of this data. While anomaly detection has been widely studied in the context of network data, operational data presents several new challenges, including the volatility and sparseness of data, and the need to perform fast detection (complicating application of schemes that require offline processing or large/stable data sets to converge). To address these challenges, we propose Tiresias, an automated approach to locating anomalous events on hierarchical operational data. Tiresias leverages the hierarchical structure of operational data to identify high-impact aggregates (e.g., locations in the network, failure modes) likely to be associated with anomalous events. To accommodate different kinds of operational network data, Tiresias consists of an online detection algorithm with low time and space complexity, while preserving high detection accuracy. We present results from two case studies using operational data collected at a large commercial IP network operated by a Tier-1 ISP: customer care call logs and set-top box crash logs. By comparing with a reference set verified by the ISP's operational group, we validate that Tiresias can achieve >94% accuracy in locating anomalies. Tiresias also discovered several previously unknown anomalies in the ISP's customer care cases, demonstrating its effectiveness.
On the Mixing Time of Markov Chain Monte Carlo for Integer Least-Square Problems
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we study the mixing time of Markov Chain Monte Carlo (MCMC) for integer least-square (LS) optimization problems. It is found that the mixing time of MCMC for integer LS problems depends on the structure of the underlying lattice. More specifically, the mixing time of MCMC is closely related to whether there is a local minimum in the lattice structure. For some lattices, the mixing time of the Markov chain is independent of the signal-to-noise ($SNR$) ratio and grows polynomially in the problem dimension; while for some lattices, the mixing time grows unboundedly as $SNR$ grows. Both theoretical and empirical results suggest that to ensure fast mixing, the temperature for MCMC should often grow positively as the $SNR$ increases. We also derive the probability that there exist local minima in an integer least-square problem, which can be as high as $1/3-\frac{1}{\sqrt{5}}+\frac{2\arctan(\sqrt{5/3})}{\sqrt{5}π}$.
An Optimum Time Quantum Using Linguistic Synthesis for Round Robin Scheduling Algorithm
Venue: arXiv cs.OH 2012
Year: 2012

In Round Robin CPU scheduling algorithm the main concern is with the size of time quantum and the increased waiting and turnaround time. Decision for these is usually based on parameters which are assumed to be precise. However, in many cases the values of these parameters are vague and imprecise. The performance of fuzzy logic depends upon the ability to deal with Linguistic variables. With this intent, this paper attempts to generate an Optimal Time Quantum dynamically based on the parameters which are treated as Linguistic variables. This paper also includes Mamdani Fuzzy Inference System using Trapezoidal membership function, results in LRRTQ Fuzzy Inference System. In this paper, we present an algorithm to improve the performance of round robin scheduling algorithm. Numerical analysis based on LRRTQ results on proposed algorithm show the improvement in the performance of the system by reducing unnecessary context switches and also by providing reasonable turnaround time.