OpenRaiser/Intern-Atlas huggingface dataset:
Combinatorial information distance
Venue: arXiv cs.DM 2010
Year: 2010

Let $|A|$ denote the cardinality of a finite set $A$. For any real number $x$ define $t(x)=x$ if $x\geq1$ and 1 otherwise. For any finite sets $A,B$ let $δ(A,B)$ $=$ $\log_{2}(t(|B\cap\bar{A}||A|))$. We define {This appears as Technical Report # arXiv:0905.2386v4. A shorter version appears in the {Proc. of Mini-Conference on Applied Theoretical Computer Science (MATCOS-10)}, Slovenia, Oct. 13-14, 2010.} a new cobinatorial distance $d(A,B)$ $=$ $\max\{δ(A,B),δ(B,A)\} $ which may be applied to measure the distance between binary strings of different lengths. The distance is based on a classical combinatorial notion of information introduced by Kolmogorov.
On Active Learning and Supervised Transmission of Spectrum Sharing Based Cognitive Radios by Exploiting Hidden Primary Radio Feedback
Venue: arXiv cs.IT 2010
Year: 2010

This paper studies the wireless spectrum sharing between a pair of distributed primary radio (PR) and cognitive radio (CR) links. Assuming that the PR link adapts its transmit power and/or rate upon receiving an interference signal from the CR and such transmit adaptations are observable by the CR, this results in a new form of feedback from the PR to CR, refereed to as hidden PR feedback, whereby the CR learns the PR's strategy for transmit adaptations without the need of a dedicated feedback channel from the PR. In this paper, we exploit the hidden PR feedback to design new learning and transmission schemes for spectrum sharing based CRs, namely active learning and supervised transmission. For active learning, the CR initiatively sends a probing signal to interfere with the PR, and from the observed PR transmit adaptations the CR estimates the channel gain from its transmitter to the PR receiver, which is essential for the CR to control its interference to the PR during the subsequent data transmission. This paper proposes a new transmission protocol for the CR to implement the active learning and the solutions to deal with various practical issues for implementation, such as time synchronization, rate estimation granularity, power measurement noise, and channel variation. Furthermore, with the acquired knowledge from active learning, the CR designs a supervised data transmission by effectively controlling the interference powers both to and from the PR, so as to achieve the optimum performance tradeoffs for the PR and CR links. Numerical results are provided to evaluate the effectiveness of the proposed schemes for CRs under different system setups.
Profiling of a network behind an infectious disease outbreak
Venue: arXiv cs.AI 2010
Year: 2010

Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stochastic spreads over the network from a dataset on an infectious disease outbreak in the early growth phase. Populations in a combination of epidemiological compartment models and a meta-population network model are described by stochastic differential equations. Probability density functions are derived from the equations and used for the maximal likelihood estimation of the topology and parameters. The method is tested with computationally synthesized datasets and the WHO dataset on SARS outbreak.
Turbo Packet Combining Strategies for the MIMO-ISI ARQ Channel
Venue: arXiv cs.IT 2010
Year: 2010

This paper addresses the issue of efficient turbo packet combining techniques for coded transmission with a Chase-type automatic repeat request (ARQ) protocol operating over a multiple-input--multiple-output (MIMO) channel with intersymbol interference (ISI). First of all, we investigate the outage probability and the outage-based power loss of the MIMO-ISI ARQ channel when optimal maximum a posteriori (MAP) turbo packet combining is used at the receiver. We show that the ARQ delay (i.e., the maximum number of ARQ rounds) does not completely translate into a diversity gain. We then introduce two efficient turbo packet combining algorithms that are inspired by minimum mean square error (MMSE)-based turbo equalization techniques. Both schemes can be viewed as low-complexity versions of the optimal MAP turbo combiner. The first scheme is called signal-level turbo combining and performs packet combining and multiple transmission ISI cancellation jointly at the signal-level. The second scheme, called symbol-level turbo combining, allows ARQ rounds to be separately turbo equalized, while combining is performed at the filter output. We conduct a complexity analysis where we demonstrate that both algorithms have almost the same computational cost as the conventional log-likelihood ratio (LLR)-level combiner. Simulation results show that both proposed techniques outperform LLR-level combining, while for some representative MIMO configurations, signal-level combining has better ISI cancellation capability and achievable diversity order than that of symbol-level combining.
Medium Access Control Protocols With Memory
Venue: arXiv cs.NI 2010
Year: 2010

Many existing medium access control (MAC) protocols utilize past information (e.g., the results of transmission attempts) to adjust the transmission parameters of users. This paper provides a general framework to express and evaluate distributed MAC protocols utilizing a finite length of memory for a given form of feedback information. We define protocols with memory in the context of a slotted random access network with saturated arrivals. We introduce two performance metrics, throughput and average delay, and formulate the problem of finding an optimal protocol. We first show that a TDMA outcome, which is the best outcome in the considered scenario, can be obtained after a transient period by a protocol with (N-1)-slot memory, where N is the total number of users. Next, we analyze the performance of protocols with 1-slot memory using a Markov chain and numerical methods. Protocols with 1-slot memory can achieve throughput arbitrarily close to 1 (i.e., 100% channel utilization) at the expense of large average delay, by correlating successful users in two consecutive slots. Finally, we apply our framework to wireless local area networks.
Minimal Gröbner bases and the predictable leading monomial property
Venue: arXiv cs.IT 2010
Year: 2010

We focus on Gröbner bases for modules of univariate polynomial vectors over a ring. We identify a useful property, the "predictable leading monomial (PLM) property" that is shared by minimal Gröbner bases of modules in F[x]^q, no matter what positional term order is used. The PLM property is useful in a range of applications and can be seen as a strengthening of the wellknown predictable degree property (= row reducedness), a terminology introduced by Forney in the 70's. Because of the presence of zero divisors, minimal Gröbner bases over a finite ring of the type Z_p^r (where p is a prime integer and r is an integer >1) do not necessarily have the PLM property. In this paper we show how to derive, from an ordered minimal Gröbner basis, a so-called "minimal Gröbner p-basis" that does have a PLM property. We demonstrate that minimal Gröbner p-bases lend themselves particularly well to derive minimal realization parametrizations over Z_p^r. Applications are in coding and sequences over Z_p^r.
Asymmetric Traveling Salesman Path and Directed Latency Problems
Venue: arXiv cs.DS 2010
Year: 2010

We study integrality gaps and approximability of two closely related problems on directed graphs. Given a set V of n nodes in an underlying asymmetric metric and two specified nodes s and t, both problems ask to find an s-t path visiting all other nodes. In the asymmetric traveling salesman path problem (ATSPP), the objective is to minimize the total cost of this path. In the directed latency problem, the objective is to minimize the sum of distances on this path from s to each node. Both of these problems are NP-hard. The best known approximation algorithms for ATSPP had ratio O(log n) until the very recent result that improves it to O(log n/ log log n). However, only a bound of O(sqrt(n)) for the integrality gap of its linear programming relaxation has been known. For directed latency, the best previously known approximation algorithm has a guarantee of O(n^(1/2+eps)), for any constant eps > 0. We present a new algorithm for the ATSPP problem that has an approximation ratio of O(log n), but whose analysis also bounds the integrality gap of the standard LP relaxation of ATSPP by the same factor. This solves an open problem posed by Chekuri and Pal [2007]. We then pursue a deeper study of this linear program and its variations, which leads to an algorithm for the k-person ATSPP (where k s-t paths of minimum total length are sought) and an O(log n)-approximation for the directed latency problem.
Beyond No Free Lunch: Realistic Algorithms for Arbitrary Problem Classes
Venue: arXiv cs.IT 2010
Year: 2010

We show how the necessary and sufficient conditions for the NFL to apply can be reduced to the single requirement of the set of objective functions under consideration being closed under permutation, and quantify the extent to which a set of objectives not closed under permutation can give rise to a performance difference between two algorithms. Then we provide a more refined definition of performance under which we show that revisiting algorithms are always trumped by enumerative ones.
On semifast Fourier transform algorithms
Venue: arXiv cs.IT 2010
Year: 2010

We consider the relations between well-known Fourier transform algorithms.
An Efficient Algorithm for Factoring Polynomials over Algebraic Extension Field
Venue: arXiv cs.SC 2010
Year: 2010

A new efficient algorithm is proposed for factoring polynomials over an algebraic extension field. The extension field is defined by a polynomial ring modulo a maximal ideal. If the maximal ideal is given by its Groebner basis, no extra Groebner basis computation is needed for factoring a polynomial over this extension field. Nothing more than linear algebraic technique is used to get a polynomial over the ground field by a generic linear map. Then this polynomial is factorized over the ground field. From these factors, the factorization of the polynomial over the extension field is obtained. The new algorithm has been implemented and computer experiments indicate that the new algorithm is very efficient, particularly in complicated examples.
Sequential Posted Pricing and Multi-parameter Mechanism Design
Venue: arXiv cs.GT 2010
Year: 2010

We consider the classical mathematical economics problem of {\em Bayesian optimal mechanism design} where a principal aims to optimize expected revenue when allocating resources to self-interested agents with preferences drawn from a known distribution. In single-parameter settings (i.e., where each agent's preference is given by a single private value for being served and zero for not being served) this problem is solved [Myerson '81]. Unfortunately, these single parameter optimal mechanisms are impractical and rarely employed [Ausubel and Milgrom '06], and furthermore the underlying economic theory fails to generalize to the important, relevant, and unsolved multi-dimensional setting (i.e., where each agent's preference is given by multiple values for each of the multiple services available) [Manelli and Vincent '07]. In contrast to the theory of optimal mechanisms we develop a theory of sequential posted price mechanisms, where agents in sequence are offered take-it-or-leave-it prices. These mechanisms are approximately optimal in single-dimensional settings, and avoid many of the properties that make optimal mechanisms impractical. Furthermore, these mechanisms generalize naturally to give the first known approximations to the elusive optimal multi-dimensional mechanism design problem. In particular, we solve multi-dimensional multi-unit auction problems and generalizations to matroid feasibility constraints. The constant approximations we obtain range from 1.5 to 8. For all but one case, our posted price sequences can be computed in polynomial time.
Living at the Edge: A Large Deviations Approach to the Outage MIMO Capacity
Venue: arXiv cs.IT 2010
Year: 2010

Using a large deviations approach we calculate the probability distribution of the mutual information of MIMO channels in the limit of large antenna numbers. In contrast to previous methods that only focused at the distribution close to its mean (thus obtaining an asymptotically Gaussian distribution), we calculate the full distribution, including its tails which strongly deviate from the Gaussian behavior near the mean. The resulting distribution interpolates seamlessly between the Gaussian approximation for rates $R$ close to the ergodic value of the mutual information and the approach of Zheng and Tse for large signal to noise ratios $ρ$. This calculation provides us with a tool to obtain outage probabilities analytically at any point in the $(R, ρ, N)$ parameter space, as long as the number of antennas $N$ is not too small. In addition, this method also yields the probability distribution of eigenvalues constrained in the subspace where the mutual information per antenna is fixed to $R$ for a given $ρ$. Quite remarkably, this eigenvalue density is of the form of the Marcenko-Pastur distribution with square-root singularities, and it depends on the values of $R$ and $ρ$.
A numerical study of fluids with pressure dependent viscosity flowing through a rigid porous medium
Venue: arXiv cs.NA 2010
Year: 2010

In this paper we consider modifications to Darcy's equation wherein the drag coefficient is a function of pressure, which is a realistic model for technological applications like enhanced oil recovery and geological carbon sequestration. We first outline the approximations behind Darcy's equation and the modifications that we propose to Darcy's equation, and derive the governing equations through a systematic approach using mixture theory. We then propose a stabilized mixed finite element formulation for the modified Darcy's equation. To solve the resulting nonlinear equations we present a solution procedure based on the consistent Newton-Raphson method. We solve representative test problems to illustrate the performance of the proposed stabilized formulation. One of the objectives of this paper is also to show that the dependence of viscosity on the pressure can have a significant effect both on the qualitative and quantitative nature of the solution.
A Short Note on Compressed Sensing with Partially Known Signal Support
Venue: arXiv cs.IT 2010
Year: 2010

This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear measurements when the signal support is partially known. The reconstruction method is based on a convex minimization program coined "innovative Basis Pursuit DeNoise" (or iBPDN). Under the common $\ell_2$-fidelity constraint made on the available measurements, this optimization promotes the ($\ell_1$) sparsity of the candidate signal over the complement of this known part. In particular, this paper extends the results of Vaswani et al. to the cases of compressible signals and noisy measurements. Our proof relies on a small adaption of the results of Candes in 2008 for characterizing the stability of the Basis Pursuit DeNoise (BPDN) program. We emphasize also an interesting link between our method and the recent work of Davenport et al. on the $δ$-stable embeddings and the "cancel-then-recover" strategy applied to our problem. For both approaches, reconstructions are indeed stabilized when the sensing matrix respects the Restricted Isometry Property for the same sparsity order. We conclude by sketching an easy numerical method relying on monotone operator splitting and proximal methods that iteratively solves iBPDN.
A Strong Direct Product Theorem for Disjointness
Venue: arXiv cs.CC 2010
Year: 2010

A strong direct product theorem states that if we want to compute $k$ independent instances of a function, using less than $k$ times the resources needed for one instance, then the overall success probability will be exponentially small in $k$. We establish such a theorem for the randomized communication complexity of the Disjointness problem, i.e., with communication $const\cdot kn$ the success probability of solving $k$ instances of size $n$ can only be exponentially small in $k$. We show that this bound even holds for $AM$ communication protocols with limited ambiguity. This also implies a new lower bound for Disjointness in a restricted 3-player NOF protocol, and optimal communication-space tradeoffs for Boolean matrix product. Our main result follows from a solution to the dual of a linear programming problem, whose feasibility comes from a so-called Intersection Sampling Lemma that generalizes a result by Razborov.
Notes on large angle crossing graphs
Venue: arXiv cs.DS 2010
Year: 2010

A graph G is an a-angle crossing (aAC) graph if every pair of crossing edges in G intersect at an angle of at least a. The concept of right angle crossing (RAC) graphs (a=Pi/2) was recently introduced by Didimo et. al. It was shown that any RAC graph with n vertices has at most 4n-10 edges and that there are infinitely many values of n for which there exists a RAC graph with n vertices and 4n-10 edges. In this paper, we give upper and lower bounds for the number of edges in aAC graphs for all 0 < a < Pi/2.
Distributed Source Coding for Correlated Memoryless Gaussian Sources
Venue: arXiv cs.IT 2010
Year: 2010

We consider a distributed source coding problem of $L$ correlated Gaussian observations $Y_i, i=1,2,...,L$. We assume that the random vector $Y^{L}={}^{\rm t} (Y_1,Y_2,$ $...,Y_L)$ is an observation of the Gaussian random vector $X^K={}^{\rm t}(X_1,X_2,...,X_K)$, having the form $Y^L=AX^K+N^L ,$ where $A$ is a $L\times K$ matrix and $N^L={}^{\rm t}(N_1,N_2,...,N_L)$ is a vector of $L$ independent Gaussian random variables also independent of $X^K$. The estimation error on $X^K$ is measured by the distortion covariance matrix. The rate distortion region is defined by a set of all rate vectors for which the estimation error is upper bounded by an arbitrary prescribed covariance matrix in the meaning of positive semi definite. In this paper we derive explicit outer and inner bounds of the rate distortion region. This result provides a useful tool to study the direct and indirect source coding problems on this Gaussian distributed source coding system, which remain open in general.
How does certainty enter into the mind?
Venue: arXiv cs.OH 2010
Year: 2010

Any problem is concerned with the mind, but what do minds make a decision on? Here we show that there are three conditions for the mind to make a certain answer. We found that some difficulties in physics and mathematics are in fact introduced by infinity, which can not be rightly expressed by minds. Based on this point, we suggest a general observation system, where we use region (a type of infinity) to substitute for infinitesimal (another type of infinity) and thus get a consistent image with the mind. Furthermore, we declare that without world pictures we can never have ideas to any expressive events, which is the primary condition for a wave function like mind to collapse to a series of numbers. A following observation by expanding algorithm brings the final collapse: classifying the numbers and coming up with a certain yes or no answer.
The Shield that Never Was: Societies with Single-Peaked Preferences are More Open to Manipulation and Control
Venue: arXiv cs.GT 2010
Year: 2010

Much work has been devoted, during the past twenty years, to using complexity to protect elections from manipulation and control. Many results have been obtained showing NP-hardness shields, and recently there has been much focus on whether such worst-case hardness protections can be bypassed by frequently correct heuristics or by approximations. This paper takes a very different approach: We argue that when electorates follow the canonical political science model of societal preferences the complexity shield never existed in the first place. In particular, we show that for electorates having single-peaked preferences, many existing NP-hardness results on manipulation and control evaporate.
Exploiting Unlabeled Data to Enhance Ensemble Diversity
Venue: arXiv cs.LG 2010
Year: 2010

Ensemble learning aims to improve generalization ability by using multiple base learners. It is well-known that to construct a good ensemble, the base learners should be accurate as well as diverse. In this paper, unlabeled data is exploited to facilitate ensemble learning by helping augment the diversity among the base learners. Specifically, a semi-supervised ensemble method named UDEED is proposed. Unlike existing semi-supervised ensemble methods where error-prone pseudo-labels are estimated for unlabeled data to enlarge the labeled data to improve accuracy, UDEED works by maximizing accuracies of base learners on labeled data while maximizing diversity among them on unlabeled data. Experiments show that UDEED can effectively utilize unlabeled data for ensemble learning and is highly competitive to well-established semi-supervised ensemble methods.
Method of resolution of 3SAT in polynomial time
Venue: arXiv cs.CC 2010
Year: 2010

Presentation of a Method for determining whether a problem 3Sat has solution, and if yes to find one, in time max O(n^15). Is thus proved that the problem 3Sat is fully resolved in polynomial time and therefore that it is in P, by the work of Cook and Levin, and can transform a SAT problem in a 3Sat in polynomial time (ref. Karp), it follows that P = NP. Open Source program is available at http://www.visainformatica.it/3sat
A regularity lemma, and low-weight approximators, for low-degree polynomial threshold functions
Venue: arXiv cs.CC 2010
Year: 2010

We give a "regularity lemma" for degree-d polynomial threshold functions (PTFs) over the Boolean cube {-1,1}^n. This result shows that every degree-d PTF can be decomposed into a constant number of subfunctions such that almost all of the subfunctions are close to being regular PTFs. Here a "regular PTF is a PTF sign(p(x)) where the influence of each variable on the polynomial p(x) is a small fraction of the total influence of p. As an application of this regularity lemma, we prove that for any constants d \geq 1, \eps \geq 0, every degree-d PTF over n variables has can be approximated to accuracy eps by a constant-degree PTF that has integer weights of total magnitude O(n^d). This weight bound is shown to be optimal up to constant factors.
Optimal Feedback Communication via Posterior Matching
Venue: arXiv cs.IT 2010
Year: 2010

In this paper we introduce a fundamental principle for optimal communication over general memoryless channels in the presence of noiseless feedback, termed posterior matching. Using this principle, we devise a (simple, sequential) generic feedback transmission scheme suitable for a large class of memoryless channels and input distributions, achieving any rate below the corresponding mutual information. This provides a unified framework for optimal feedback communication in which the Horstein scheme (BSC) and the Schalkwijk-Kailath scheme (AWGN channel) are special cases. Thus, as a corollary, we prove that the Horstein scheme indeed attains the BSC capacity, settling a longstanding conjecture. We further provide closed form expressions for the error probability of the scheme over a range of rates, and derive the achievable rates in a mismatch setting where the scheme is designed according to the wrong channel model. Several illustrative examples of the posterior matching scheme for specific channels are given, and the corresponding error probability expressions are evaluated. The proof techniques employed utilize novel relations between information rates and contraction properties of iterated function systems.