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Title: Online Learning via Sequential Complexities |
Abstract: We consider the problem of sequential prediction and provide tools to study the minimax value of the associated game. Classical statistical learning theory provides several useful complexity measures to study learning with i.i.d. data. Our proposed sequential complexities can be seen as extensions of these me... |
Title: Sparse covariance thresholding for high-dimensional variable selection |
Abstract: In high-dimensions, many variable selection methods, such as the lasso, are often limited by excessive variability and rank deficiency of the sample covariance matrix. Covariance sparsity is a natural phenomenon in high-dimensional applications, such as microarray analysis, image processing, etc., in which a ... |
Title: Biometric Authentication using Nonparametric Methods |
Abstract: The physiological and behavioral trait is employed to develop biometric authentication systems. The proposed work deals with the authentication of iris and signature based on minimum variance criteria. The iris patterns are preprocessed based on area of the connected components. The segmented image used for a... |
Title: Game Information System |
Abstract: In this Information system age many organizations consider information system as their weapon to compete or gain competitive advantage or give the best services for non profit organizations. Game Information System as combining Information System and game is breakthrough to achieve organizations' performance.... |
Title: Regression on fixed-rank positive semidefinite matrices: a Riemannian approach |
Abstract: The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms a... |
Title: Uncovering the Riffled Independence Structure of Rankings |
Abstract: Representing distributions over permutations can be a daunting task due to the fact that the number of permutations of $n$ objects scales factorially in $n$. One recent way that has been used to reduce storage complexity has been to exploit probabilistic independence, but as we argue, full independence assump... |
Title: Segmentation and Nodal Points in Narrative: Study of Multiple Variations of a Ballad |
Abstract: The Lady Maisry ballads afford us a framework within which to segment a storyline into its major components. Segments and as a consequence nodal points are discussed for nine different variants of the Lady Maisry story of a (young) woman being burnt to death by her family, on account of her becoming pregnant ... |
Title: C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework |
Abstract: Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an L1-regularized linear regression problem, commonly referred to as Lasso or Basis Pursuit. In this work we combine the sparsity-inducing property of the Lasso model at ... |
Title: Copula Processes |
Abstract: We define a copula process which describes the dependencies between arbitrarily many random variables independently of their marginal distributions. As an example, we develop a stochastic volatility model, Gaussian Copula Process Volatility (GCPV), to predict the latent standard deviations of a sequence of ra... |
Title: Begin, After, and Later: a Maximal Decidable Interval Temporal Logic |
Abstract: Interval temporal logics (ITLs) are logics for reasoning about temporal statements expressed over intervals, i.e., periods of time. The most famous ITL studied so far is Halpern and Shoham's HS, which is the logic of the thirteen Allen's interval relations. Unfortunately, HS and most of its fragments have an ... |
Title: Computing by Means of Physics-Based Optical Neural Networks |
Abstract: We report recent research on computing with biology-based neural network models by means of physics-based opto-electronic hardware. New technology provides opportunities for very-high-speed computation and uncovers problems obstructing the wide-spread use of this new capability. The Computation Modeling commu... |
Title: The Deterministic Dendritic Cell Algorithm |
Abstract: The Dendritic Cell Algorithm is an immune-inspired algorithm orig- inally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to ... |
Title: The coalescent and its descendants |
Abstract: The coalescent revolutionised theoretical population genetics, simplifying, or making possible for the first time, many analyses, proofs, and derivations, and offering crucial insights about the way in which the structure of data in samples from populations depends on the demographic history of the population... |
Title: The DCA:SOMe Comparison A comparative study between two biologically-inspired algorithms |
Abstract: The Dendritic Cell Algorithm (DCA) is an immune-inspired algorithm, developed for the purpose of anomaly detection. The algorithm performs multi-sensor data fusion and correlation which results in a 'context aware' detection system. Previous applications of the DCA have included the detection of potentially m... |
Title: The Motif Tracking Algorithm |
Abstract: The search for patterns or motifs in data represents a problem area of key interest to finance and economic researchers. In this paper we introduce the Motif Tracking Algorithm, a novel immune inspired pattern identification tool that is able to identify unknown motifs of a non specified length which repeat w... |
Title: New worst upper bound for #SAT |
Abstract: The rigorous theoretical analyses of algorithms for #SAT have been proposed in the literature. As we know, previous algorithms for solving #SAT have been analyzed only regarding the number of variables as the parameter. However, the time complexity for solving #SAT instances depends not only on the number of ... |
Title: ToLeRating UR-STD |
Abstract: A new emerging paradigm of Uncertain Risk of Suspicion, Threat and Danger, observed across the field of information security, is described. Based on this paradigm a novel approach to anomaly detection is presented. Our approach is based on a simple yet powerful analogy from the innate part of the human immune... |
Title: Testing randomness of spatial point patterns with the Ripley statistic |
Abstract: Aggregation patterns are often visually detected in sets of location data. These clusters may be the result of interesting dynamics or the effect of pure randomness. We build an asymptotically Gaussian test for the hypothesis of randomness corresponding to a Poisson point process. We first compute the exact f... |
Title: Towards a Conceptual Framework for Innate Immunity |
Abstract: Innate immunity now occupies a central role in immunology. However, artificial immune system models have largely been inspired by adaptive not innate immunity. This paper reviews the biological principles and properties of innate immunity and, adopting a conceptual framework, asks how these can be incorporate... |
Title: Asymptotic Properties of Self-Normalized Linear Processes with Long Memory |
Abstract: In this paper we study the convergence to fractional Brownian motion for long memory time series having independent innovations with infinite second moment. For the sake of applications we derive the self-normalized version of this theorem. The study is motivated by models arising in economical applications w... |
Title: Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret |
Abstract: The problem of distributed learning and channel access is considered in a cognitive network with multiple secondary users. The availability statistics of the channels are initially unknown to the secondary users and are estimated using sensing decisions. There is no explicit information exchange or prior agre... |
Title: Towards the Design of Heuristics by Means of Self-Assembly |
Abstract: The current investigations on hyper-heuristics design have sprung up in two different flavours: heuristics that choose heuristics and heuristics that generate heuristics. In the latter, the goal is to develop a problem-domain independent strategy to automatically generate a good performing heuristic for the p... |
Title: Measuring interesting rules in Characteristic rule |
Abstract: Finding interesting rule in the sixth strategy step about threshold control on generalized relations in attribute oriented induction, there is possibility to select candidate attribute for further generalization and merging of identical tuples until the number of tuples is no greater than the threshold value,... |
Title: Virtual information system on working area |
Abstract: In order to get strategic positioning for competition in business organization, the information system must be ahead in this information age where the information as one of the weapons to win the competition and in the right hand the information will become a right bullet. The information system with the info... |
Title: Indonesian Earthquake Decision Support System |
Abstract: Earthquake DSS is an information technology environment which can be used by government to sharpen, make faster and better the earthquake mitigation decision. Earthquake DSS can be delivered as E-government which is not only for government itself but in order to guarantee each citizen's rights for education, ... |
Title: Calibration and Internal no-Regret with Partial Monitoring |
Abstract: Calibrated strategies can be obtained by performing strategies that have no internal regret in some auxiliary game. Such strategies can be constructed explicitly with the use of Blackwell's approachability theorem, in an other auxiliary game. We establish the converse: a strategy that approaches a convex $B$-... |
Title: Measuring Meaning on the World-Wide Web |
Abstract: We introduce the notion of the 'meaning bound' of a word with respect to another word by making use of the World-Wide Web as a conceptual environment for meaning. The meaning of a word with respect to another word is established by multiplying the product of the number of webpages containing both words by the... |
Title: Landau Theory of Adaptive Integration in Computational Intelligence |
Abstract: Computational Intelligence (CI) is a sub-branch of Artificial Intelligence paradigm focusing on the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments. There are several paradigms of CI [like artificial neural networks, evolutionary computations, swa... |
Title: On-line Spot Volatility-Estimation and Decomposition with Nonlinear Market Microstructure Noise Models |
Abstract: A technique for on-line estimation of spot volatility for high-frequency data is developed. The algorithm works directly on the transaction data and updates the volatility estimate immediately after the occurrence of a new transaction. Furthermore, a nonlinear market microstructure noise model is proposed tha... |
Title: Auxiliary Particle filtering within adaptive Metropolis-Hastings Sampling |
Abstract: Our article deals with Bayesian inference for a general state space model with the simulated likelihood computed by the particle filter. We show empirically that the partially or fully adapted particle filters can be much more efficient than the standard particle, especially when the signal to noise ratio is ... |
Title: Building Computer Network Attacks |
Abstract: In this work we start walking the path to a new perspective for viewing cyberwarfare scenarios, by introducing conceptual tools (a formal model) to evaluate the costs of an attack, to describe the theater of operations, targets, missions, actions, plans and assets involved in cyberwarfare attacks. We also des... |
Title: The Pet-Fish problem on the World-Wide Web |
Abstract: We identify the presence of Pet-Fish problem situations and the corresponding Guppy effect of concept theory on the World-Wide Web. For this purpose, we introduce absolute weights for words expressing concepts and relative weights between words expressing concepts, and the notion of 'meaning bound' between tw... |
Title: Characterization of a subclass of Tweedie distributions by a property of generalized stability |
Abstract: We introduce a class of distributions originating from an exponential family and having a property related to the strict stability property. A characteristic function representation for this family is obtained and its properties are investigated. The proposed class relates to stable distributions and includes... |
Title: Dyadic Prediction Using a Latent Feature Log-Linear Model |
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