OpenRaiser/Intern-Atlas huggingface dataset:
Decomposition During Search for Propagation-Based Constraint Solvers
Venue: arXiv cs.AI 2008
Year: 2008

We describe decomposition during search (DDS), an integration of And/Or tree search into propagation-based constraint solvers. The presented search algorithm dynamically decomposes sub-problems of a constraint satisfaction problem into independent partial problems, avoiding redundant work. The paper discusses how DDS interacts with key features that make propagation-based solvers successful: constraint propagation, especially for global constraints, and dynamic search heuristics. We have implemented DDS for the Gecode constraint programming library. Two applications, solution counting in graph coloring and protein structure prediction, exemplify the benefits of DDS in practice.
An Approximation Ratio for Biclustering
Venue: arXiv cs.DS 2008
Year: 2008

The problem of biclustering consists of the simultaneous clustering of rows and columns of a matrix such that each of the submatrices induced by a pair of row and column clusters is as uniform as possible. In this paper we approximate the optimal biclustering by applying one-way clustering algorithms independently on the rows and on the columns of the input matrix. We show that such a solution yields a worst-case approximation ratio of 1+sqrt(2) under L1-norm for 0-1 valued matrices, and of 2 under L2-norm for real valued matrices.
Middleware-based Database Replication: The Gaps between Theory and Practice
Venue: arXiv cs.DB 2008
Year: 2008

The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.
Low SNR Capacity of Noncoherent Fading Channels
Venue: arXiv cs.IT 2008
Year: 2008

Discrete-time Rayleigh fading single-input single-output (SISO) and multiple-input multiple-output (MIMO) channels are considered, with no channel state information at the transmitter or the receiver. The fading is assumed to be stationary and correlated in time, but independent from antenna to antenna. Peak-power and average-power constraints are imposed on the transmit antennas. For MIMO channels, these constraints are either imposed on the sum over antennas, or on each individual antenna. For SISO channels and MIMO channels with sum power constraints, the asymptotic capacity as the peak signal-to-noise ratio tends to zero is identified; for MIMO channels with individual power constraints, this asymptotic capacity is obtained for a class of channels called transmit separable channels. The results for MIMO channels with individual power constraints are carried over to SISO channels with delay spread (i.e. frequency selective fading).
The capacity of a class of 3-receiver broadcast channels with degraded message sets
Venue: arXiv cs.IT 2008
Year: 2008

Korner and Marton established the capacity region for the 2-receiver broadcast channel with degraded message sets. Recent results and conjectures suggest that a straightforward extension of the Korner-Marton region to more than 2 receivers is optimal. This paper shows that this is not the case. We establish the capacity region for a class of 3-receiver broadcast channels with 2 degraded message sets and show that it can be strictly larger than the straightforward extension of the Korner-Marton region. The key new idea is indirect decoding, whereby a receiver who cannot directly decode a cloud center, finds it indirectly by decoding satellite codewords. This idea is then used to establish new inner and outer bounds on the capacity region of the general 3-receiver broadcast channel with 2 and 3 degraded message sets. We show that these bounds are tight for some nontrivial cases. The results suggest that the capacity of the 3-receiver broadcast channel with degraded message sets is as at least as hard to find as the capacity of the general 2-receiver broadcast channel with common and private message.
Explicit Non-Adaptive Combinatorial Group Testing Schemes
Venue: arXiv cs.DS 2008
Year: 2008

Group testing is a long studied problem in combinatorics: A small set of $r$ ill people should be identified out of the whole ($n$ people) by using only queries (tests) of the form "Does set X contain an ill human?". In this paper we provide an explicit construction of a testing scheme which is better (smaller) than any known explicit construction. This scheme has $\bigT{\min[r^2 \ln n,n]}$ tests which is as many as the best non-explicit schemes have. In our construction we use a fact that may have a value by its own right: Linear error-correction codes with parameters $[m,k,δm]_q$ meeting the Gilbert-Varshamov bound may be constructed quite efficiently, in $\bigT{q^km}$ time.
Computer algebra in systems biology
Venue: arXiv cs.SC 2008
Year: 2008

Systems biology focuses on the study of entire biological systems rather than on their individual components. With the emergence of high-throughput data generation technologies for molecular biology and the development of advanced mathematical modeling techniques, this field promises to provide important new insights. At the same time, with the availability of increasingly powerful computers, computer algebra has developed into a useful tool for many applications. This article illustrates the use of computer algebra in systems biology by way of a well-known gene regulatory network, the Lac Operon in the bacterium E. coli.
On the Length of the Wadge Hierarchy of Omega Context Free Languages
Venue: arXiv cs.LO 2008
Year: 2008

We prove in this paper that the length of the Wadge hierarchy of omega context free languages is greater than the Cantor ordinal epsilon_omega, which is the omega-th fixed point of the ordinal exponentiation of base omega. The same result holds for the conciliating Wadge hierarchy, defined by J. Duparc, of infinitary context free languages, studied by D. Beauquier. We show also that there exist some omega context free languages which are Sigma^0_omega-complete Borel sets, improving previous results on omega context free languages and the Borel hierarchy.
A Flexible and Secure Remote Systems Authentication Scheme Using Smart Cards
Venue: arXiv cs.CR 2008
Year: 2008

The paper presents an authentication scheme for remote systems using smart card. The scheme prevents the scenario of many logged in users with the same login identity, and does not require password/verifier table to validate the users' login request. The scheme provides a user-friendly password change option, and withstands the replay, impersonation, stolen-verifier, guessing, and denial-of-service attacks.
An algorithm for finding the Independence Number of a graph
Venue: arXiv cs.DM 2008
Year: 2008

In this paper, we prove that for every connected graph G, there exists a split graph H with the same independence number and the same order. Then we propose a first algorithm for finding this graph, given the degree sequence of the input graph G. Further, we propose a second algorithm for finding the independence number of G, given the adjacency matrix of G.
Adversarial Models and Resilient Schemes for Network Coding
Venue: arXiv cs.IT 2008
Year: 2008

In a recent paper, Jaggi et al. (INFOCOM 2007), presented a distributed polynomial-time rate-optimal network-coding scheme that works in the presence of Byzantine faults. We revisit their adversarial models and augment them with three, arguably realistic, models. In each of the models, we present a distributed scheme that demonstrates the usefulness of the model. In particular, all of the schemes obtain optimal rate $C-z$, where $C$ is the network capacity and $z$ is a bound on the number of links controlled by the adversary.
Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
Venue: arXiv cs.IT 2008
Year: 2008

The combination of source coding with decoder side-information (Wyner-Ziv problem) and channel coding with encoder side-information (Gel'fand-Pinsker problem) can be optimally solved using the separation principle. In this work we show an alternative scheme for the quadratic-Gaussian case, which merges source and channel coding. This scheme achieves the optimal performance by a applying modulo-lattice modulation to the analog source. Thus it saves the complexity of quantization and channel decoding, and remains with the task of "shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme approaches the optimal performance using an SNR-independent encoder, thus it is robust to unknown SNR at the encoder.
On the Period of a Periodic-Finite-Type Shift
Venue: arXiv cs.IT 2008
Year: 2008

Periodic-finite-type shifts (PFT's) form a class of sofic shifts that strictly contains the class of shifts of finite type (SFT's). In this paper, we investigate how the notion of "period" inherent in the definition of a PFT causes it to differ from an SFT, and how the period influences the properties of a PFT.
Coding Strategies for Noise-Free Relay Cascades with Half-Duplex Constraint
Venue: arXiv cs.IT 2008
Year: 2008

Two types of noise-free relay cascades are investigated. Networks where a source communicates with a distant receiver via a cascade of half-duplex constrained relays, and networks where not only the source but also a single relay node intends to transmit information to the same destination. We introduce two relay channel models, capturing the half-duplex constraint, and within the framework of these models capacity is determined for the first network type. It turns out that capacity is significantly higher than the rates which are achievable with a straightforward time-sharing approach. A capacity achieving coding strategy is presented based on allocating the transmit and receive time slots of a node in dependence of the node's previously received data. For the networks of the second type, an upper bound to the rate region is derived from the cut-set bound. Further, achievability of the cut-set bound in the single relay case is shown given that the source rate exceeds a certain minimum value.
Capacity of the Discrete-Time AWGN Channel Under Output Quantization
Venue: arXiv cs.IT 2008
Year: 2008

We investigate the limits of communication over the discrete-time Additive White Gaussian Noise (AWGN) channel, when the channel output is quantized using a small number of bits. We first provide a proof of our recent conjecture on the optimality of a discrete input distribution in this scenario. Specifically, we show that for any given output quantizer choice with K quantization bins (i.e., a precision of log2 K bits), the input distribution, under an average power constraint, need not have any more than K + 1 mass points to achieve the channel capacity. The cutting-plane algorithm is employed to compute this capacity and to generate optimum input distributions. Numerical optimization over the choice of the quantizer is then performed (for 2-bit and 3-bit symmetric quantization), and the results we obtain show that the loss due to low-precision output quantization, which is small at low signal-to-noise ratio (SNR) as expected, can be quite acceptable even for moderate to high SNR values. For example, at SNRs up to 20 dB, 2-3 bit quantization achieves 80-90% of the capacity achievable using infinite-precision quantization.
On the guaranteed error correction capability of LDPC codes
Venue: arXiv cs.IT 2008
Year: 2008

We investigate the relation between the girth and the guaranteed error correction capability of $γ$-left regular LDPC codes when decoded using the bit flipping (serial and parallel) algorithms. A lower bound on the number of variable nodes which expand by a factor of at least $3 γ/4$ is found based on the Moore bound. An upper bound on the guaranteed correction capability is established by studying the sizes of smallest possible trapping sets.
Capacity Bounds for the Gaussian Interference Channel
Venue: arXiv cs.IT 2008
Year: 2008

The capacity region of the two-user Gaussian Interference Channel (IC) is studied. Three classes of channels are considered: weak, one-sided, and mixed Gaussian IC. For the weak Gaussian IC, a new outer bound on the capacity region is obtained that outperforms previously known outer bounds. The sum capacity for a certain range of channel parameters is derived. For this range, it is proved that using Gaussian codebooks and treating interference as noise is optimal. It is shown that when Gaussian codebooks are used, the full Han-Kobayashi achievable rate region can be obtained by using the naive Han-Kobayashi achievable scheme over three frequency bands (equivalently, three subspaces). For the one-sided Gaussian IC, an alternative proof for the Sato's outer bound is presented. We derive the full Han-Kobayashi achievable rate region when Gaussian codebooks are utilized. For the mixed Gaussian IC, a new outer bound is obtained that outperforms previously known outer bounds. For this case, the sum capacity for the entire range of channel parameters is derived. It is proved that the full Han-Kobayashi achievable rate region using Gaussian codebooks is equivalent to that of the one-sided Gaussian IC for a particular range of channel parameters.
Stream Computing
Venue: arXiv cs.AI 2008
Year: 2008

Stream computing is the use of multiple autonomic and parallel modules together with integrative processors at a higher level of abstraction to embody "intelligent" processing. The biological basis of this computing is sketched and the matter of learning is examined.
Analyzing the Topology Types arising in a Family of Algebraic Curves Depending On Two Parameters
Venue: arXiv cs.SC 2008
Year: 2008

Given the implicit equation $F(x,y,t,s)$ of a family of algebraic plane curves depending on the parameters $t,s$, we provide an algorithm for studying the topology types arising in the family. For this purpose, the algorithm computes a finite partition of the parameter space so that the topology type of the family stays invariant over each element of the partition. The ideas contained in the paper can be seen as a generalization of the ideas in \cite{JGRS}, where the problem is solved for families of algebraic curves depending on one parameter, to the two-parameters case.
Bi-criteria Pipeline Mappings for Parallel Image Processing
Venue: arXiv cs.DC 2008
Year: 2008

Mapping workflow applications onto parallel platforms is a challenging problem, even for simple application patterns such as pipeline graphs. Several antagonistic criteria should be optimized, such as throughput and latency (or a combination). Typical applications include digital image processing, where images are processed in steady-state mode. In this paper, we study the mapping of a particular image processing application, the JPEG encoding. Mapping pipelined JPEG encoding onto parallel platforms is useful for instance for encoding Motion JPEG images. As the bi-criteria mapping problem is NP-complete, we concentrate on the evaluation and performance of polynomial heuristics.
D-optimal Bayesian Interrogation for Parameter and Noise Identification of Recurrent Neural Networks
Venue: arXiv cs.NE 2008
Year: 2008

We introduce a novel online Bayesian method for the identification of a family of noisy recurrent neural networks (RNNs). We develop Bayesian active learning technique in order to optimize the interrogating stimuli given past experiences. In particular, we consider the unknown parameters as stochastic variables and use the D-optimality principle, also known as `\emph{infomax method}', to choose optimal stimuli. We apply a greedy technique to maximize the information gain concerning network parameters at each time step. We also derive the D-optimal estimation of the additive noise that perturbs the dynamical system of the RNN. Our analytical results are approximation-free. The analytic derivation gives rise to attractive quadratic update rules.
Factored Value Iteration Converges
Venue: arXiv cs.AI 2008
Year: 2008

In this paper we propose a novel algorithm, factored value iteration (FVI), for the approximate solution of factored Markov decision processes (fMDPs). The traditional approximate value iteration algorithm is modified in two ways. For one, the least-squares projection operator is modified so that it does not increase max-norm, and thus preserves convergence. The other modification is that we uniformly sample polynomially many samples from the (exponentially large) state space. This way, the complexity of our algorithm becomes polynomial in the size of the fMDP description length. We prove that the algorithm is convergent. We also derive an upper bound on the difference between our approximate solution and the optimal one, and also on the error introduced by sampling. We analyze various projection operators with respect to their computation complexity and their convergence when combined with approximate value iteration.
Model for synchronizer of marked pairs in fork-join network
Venue: arXiv cs.DM 2008
Year: 2008

We introduce a model for synchronizer of marked pairs, which is a node for joining results of parallel processing in two-branch fork-join queueing network. A distribution for number of jobs in the synchronizer is obtained. Calculations are performed assuming that: arrivals to the network form a Poisson process, each branch operates like an M/M/N queueing system. It is shown that a mean quantity of jobs in the synchronizer is bounded below by the value, defined by parameters of the network (which contains the synchronizer) and does not depend upon performance and particular properties of the synchronizer. A domain of network parameters is found, where the flow of jobs departing from the synchronizer does not manifest a statistically significant difference from the Poisson type, despite the correlation between job flows from both branches of the fork-join network.
Design and Analysis of LDGM-Based Codes for MSE Quantization
Venue: arXiv cs.IT 2008
Year: 2008

Approaching the 1.5329-dB shaping (granular) gain limit in mean-squared error (MSE) quantization of R^n is important in a number of problems, notably dirty-paper coding. For this purpose, we start with a binary low-density generator-matrix (LDGM) code, and construct the quantization codebook by periodically repeating its set of binary codewords, or them mapped to m-ary ones with Gray mapping. The quantization algorithm is based on belief propagation, and it uses a decimation procedure to do the guessing necessary for convergence. Using the results of a true typical decimator (TTD) as reference, it is shown that the asymptotic performance of the proposed quantizer can be characterized by certain monotonicity conditions on the code's fixed point properties, which can be analyzed with density evolution, and degree distribution optimization can be carried out accordingly. When the number of iterations is finite, the resulting loss is made amenable to analysis through the introduction of a recovery algorithm from ``bad'' guesses, and the results of such analysis enable further optimization of the pace of decimation and the degree distribution. Simulation results show that the proposed LDGM-based quantizer can achieve a shaping gain of 1.4906 dB, or 0.0423 dB from the limit, and significantly outperforms trellis-coded quantization (TCQ) at a similar computational complexity.
Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels
Venue: arXiv cs.IT 2008
Year: 2008

This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any cooperation among the users, the optimization problem is formulated as a static noncooperative game of complete information. To achieve the so-called Nash equilibria of the game, we propose a new distributed algorithm called asynchronous iterative waterfilling algorithm. In this algorithm, the users update their power spectral density in a completely distributed and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received interference. The proposed algorithm represents a unified framework that encompasses and generalizes all known iterative waterfilling algorithms, e.g., sequential and simultaneous versions. The main result of the paper consists of a unified set of conditions that guarantee the global converge of the proposed algorithm to the (unique) Nash equilibrium of the game.
Construction of Z4-linear Reed-Muller codes
Venue: arXiv cs.IT 2008
Year: 2008

New quaternary Plotkin constructions are given and are used to obtain new families of quaternary codes. The parameters of the obtained codes, such as the length, the dimension and the minimum distance are studied. Using these constructions new families of quaternary Reed-Muller codes are built with the peculiarity that after using the Gray map the obtained Z4-linear codes have the same parameters and fundamental properties as the codes in the usual binary linear Reed-Muller family. To make more evident the duality relationships in the constructed families the concept of Kronecker inner product is introduced.
Human Heuristics for Autonomous Agents
Venue: arXiv cs.MA 2008
Year: 2008

We investigate the problem of autonomous agents processing pieces of information that may be corrupted (tainted). Agents have the option of contacting a central database for a reliable check of the status of the message, but this procedure is costly and therefore should be used with parsimony. Agents have to evaluate the risk of being infected, and decide if and when communicating partners are affordable. Trustability is implemented as a personal (one-to-one) record of past contacts among agents, and as a mean-field monitoring of the level of message corruption. Moreover, this information is slowly forgotten in time, so that at the end everybody is checked against the database. We explore the behavior of a homogeneous system in the case of a fixed pool of spreaders of corrupted messages, and in the case of spontaneous appearance of corrupted messages.
Analysis of Estimation of Distribution Algorithms and Genetic Algorithms on NK Landscapes
Venue: arXiv cs.NE 2008
Year: 2008

This study analyzes performance of several genetic and evolutionary algorithms on randomly generated NK fitness landscapes with various values of n and k. A large number of NK problem instances are first generated for each n and k, and the global optimum of each instance is obtained using the branch-and-bound algorithm. Next, the hierarchical Bayesian optimization algorithm (hBOA), the univariate marginal distribution algorithm (UMDA), and the simple genetic algorithm (GA) with uniform and two-point crossover operators are applied to all generated instances. Performance of all algorithms is then analyzed and compared, and the results are discussed.