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Title: Parameter identifiability and redundancy: theoretical considerations |
Abstract: In this paper we outline general considerations on parameter identifiability, and introduce the notion of weak local identifiability and gradient weak local identifiability. These are based on local properties of the likelihood, in particular the rank of the Hessian matrix. We relate these to the notions of p... |
Title: Kronecker Graphs: An Approach to Modeling Networks |
Abstract: How can we model networks with a mathematically tractable model that allows for rigorous analysis of network properties? Networks exhibit a long list of surprising properties: heavy tails for the degree distribution; small diameters; and densification and shrinking diameters over time. Most present network mo... |
Title: Importance Weighted Active Learning |
Abstract: We present a practical and statistically consistent scheme for actively learning binary classifiers under general loss functions. Our algorithm uses importance weighting to correct sampling bias, and by controlling the variance, we are able to give rigorous label complexity bounds for the learning process. Ex... |
Title: A New Clustering Algorithm Based Upon Flocking On Complex Network |
Abstract: We have proposed a model based upon flocking on a complex network, and then developed two clustering algorithms on the basis of it. In the algorithms, firstly a -nearest neighbor (knn) graph as a weighted and directed graph is produced among all data points in a dataset each of which is regarded as an agent w... |
Title: A Novel Clustering Algorithm Based Upon Games on Evolving Network |
Abstract: This paper introduces a model based upon games on an evolving network, and develops three clustering algorithms according to it. In the clustering algorithms, data points for clustering are regarded as players who can make decisions in games. On the network describing relationships among data points, an edge-... |
Title: Estimating time-varying networks |
Abstract: Stochastic networks are a plausible representation of the relational information among entities in dynamic systems such as living cells or social communities. While there is a rich literature in estimating a static or temporally invariant network from observation data, little has been done toward estimating t... |
Title: Space Alternating Penalized Kullback Proximal Point Algorithms for Maximizing Likelihood with Nondifferentiable Penalty |
Abstract: The EM algorithm is a widely used methodology for penalized likelihood estimation. Provable monotonicity and convergence are the hallmarks of the EM algorithm and these properties are well established for smooth likelihood and smooth penalty functions. However, many relaxed versions of variable selection pena... |
Title: On the Geometry of Discrete Exponential Families with Application to Exponential Random Graph Models |
Abstract: There has been an explosion of interest in statistical models for analyzing network data, and considerable interest in the class of exponential random graph (ERG) models, especially in connection with difficulties in computing maximum likelihood estimates. The issues associated with these difficulties relate ... |
Title: Exact Histogram Specification Optimized for Structural Similarity |
Abstract: An exact histogram specification (EHS) method modifies its input image to have a specified histogram. Applications of EHS include image (contrast) enhancement (e.g., by histogram equalization) and histogram watermarking. Performing EHS on an image, however, reduces its visual quality. Starting from the output... |
Title: A state-space mixed membership blockmodel for dynamic network tomography |
Abstract: In a dynamic social or biological environment, the interactions between the actors can undergo large and systematic changes. In this paper we propose a model-based approach to analyze what we will refer to as the dynamic tomography of such time-evolving networks. Our approach offers an intuitive but powerful ... |
Title: Time-Varying Networks: Recovering Temporally Rewiring Genetic Networks During the Life Cycle of Drosophila melanogaster |
Abstract: Due to the dynamic nature of biological systems, biological networks underlying temporal process such as the development of \it Drosophila melanogaster can exhibit significant topological changes to facilitate dynamic regulatory functions. Thus it is essential to develop methodologies that capture the tempora... |
Title: Dynamic Muscle Fatigue Evaluation in Virtual Working Environment |
Abstract: Musculoskeletal disorder (MSD) is one of the major health problems in mechanical work especially in manual handling jobs. Muscle fatigue is believed to be the main reason for MSD. Posture analysis techniques have been used to expose MSD risks of the work, but most of the conventional methods are only suitable... |
Title: Flexible Multivariate Density Estimation with Marginal Adaptation |
Abstract: Our article addresses the problem of flexibly estimating a multivariate density while also attempting to estimate its marginals correctly. We do so by proposing two new estimators that try to capture the best features of mixture of normals and copula estimators while avoiding some of their weaknesses. The fir... |
Title: MIMO decoding based on stochastic reconstruction from multiple projections |
Abstract: Least squares (LS) fitting is one of the most fundamental techniques in science and engineering. It is used to estimate parameters from multiple noisy observations. In many problems the parameters are known a-priori to be bounded integer valued, or they come from a finite set of values on an arbitrary finite ... |
Title: Design of a P System based Artificial Graph Chemistry |
Abstract: Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles leading to the evolution of life-like structures in an AC set up and t... |
Title: Thoughts on an Unified Framework for Artificial Chemistries |
Abstract: Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the problem of biogenesis or the origin of life. This paper presents authors thoughts towards defining a unified framework to characterize and classify symbolic artificial chemistries by... |
Title: Invariance of generalized wordlength patterns |
Abstract: The generalized wordlength pattern (GWLP) introduced by Xu and Wu (2001) for an arbitrary fractional factorial design allows one to extend the use of the minimum aberration criterion to such designs. Ai and Zhang (2004) defined the $J$-characteristics of a design and showed that they uniquely determine the de... |
Title: Information, Divergence and Risk for Binary Experiments |
Abstract: We unify f-divergences, Bregman divergences, surrogate loss bounds (regret bounds), proper scoring rules, matching losses, cost curves, ROC-curves and information. We do this by systematically studying integral and variational representations of these objects and in so doing identify their primitives which al... |
Title: From Physics to Economics: An Econometric Example Using Maximum Relative Entropy |
Abstract: Econophysics, is based on the premise that some ideas and methods from physics can be applied to economic situations. We intend to show in this paper how a physics concept such as entropy can be applied to an economic problem. In so doing, we demonstrate how information in the form of observable data and mome... |
Title: On the Optimal Convergence Probability of Univariate Estimation of Distribution Algorithms |
Abstract: In this paper, we obtain bounds on the probability of convergence to the optimal solution for the compact Genetic Algorithm (cGA) and the Population Based Incremental Learning (PBIL). We also give a sufficient condition for convergence of these algorithms to the optimal solution and compute a range of possibl... |
Title: A Step Forward in Studying the Compact Genetic Algorithm |
Abstract: The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent population instead of using traditional recombination and mutation operators. The cGA only needs a small amount of memory; therefore, ... |
Title: Quantile Mechanics II: Changes of Variables in Monte Carlo methods and GPU-Optimized Normal Quantiles |
Abstract: This article presents differential equations and solution methods for the functions of the form $Q(x) = F^-1(G(x))$, where $F$ and $G$ are cumulative distribution functions. Such functions allow the direct recycling of Monte Carlo samples from one distribution into samples from another. The method may be deve... |
Title: Contextual hypotheses and semantics of logic programs |
Abstract: Logic programming has developed as a rich field, built over a logical substratum whose main constituent is a nonclassical form of negation, sometimes coexisting with classical negation. The field has seen the advent of a number of alternative semantics, with Kripke-Kleene semantics, the well-founded semantics... |
Title: Distributed Preemption Decisions: Probabilistic Graphical Model, Algorithm and Near-Optimality |
Abstract: Cooperative decision making is a vision of future network management and control. Distributed connection preemption is an important example where nodes can make intelligent decisions on allocating resources and controlling traffic flows for multi-class service networks. A challenge is that nodal decisions are... |
Title: A Theoretical Analysis of Joint Manifolds |
Abstract: The emergence of low-cost sensor architectures for diverse modalities has made it possible to deploy sensor arrays that capture a single event from a large number of vantage points and using multiple modalities. In many scenarios, these sensors acquire very high-dimensional data such as audio signals, images,... |
Title: Estimators for Long Range Dependence: An Empirical Study |
Abstract: We present the results of a simulation study into the properties of 12 different estimators of the Hurst parameter, $H$, or the fractional integration parameter, $d$, in long memory time series. We compare and contrast their performance on simulated Fractional Gaussian Noises and fractionally integrated serie... |
Title: Approximate inference on planar graphs using Loop Calculus and Belief Propagation |
Abstract: We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006) allows to express the exact partition function of a graphical model as a finite sum of terms that can be evaluated once the belief propagation (BP)... |
Title: A new muscle fatigue and recovery model and its ergonomics application in human simulation |
Abstract: Although automatic techniques have been employed in manufacturing industries to increase productivity and efficiency, there are still lots of manual handling jobs, especially for assembly and maintenance jobs. In these jobs, musculoskeletal disorders (MSDs) are one of the major health problems due to overload... |
Title: A Fast Algorithm for Robust Regression with Penalised Trimmed Squares |
Abstract: The presence of groups containing high leverage outliers makes linear regression a difficult problem due to the masking effect. The available high breakdown estimators based on Least Trimmed Squares often do not succeed in detecting masked high leverage outliers in finite samples. An alternative to the LTS es... |
Title: A nonclassical symbolic theory of working memory, mental computations, and mental set |
Abstract: The paper tackles four basic questions associated with human brain as a learning system. How can the brain learn to (1) mentally simulate different external memory aids, (2) perform, in principle, any mental computations using imaginary memory aids, (3) recall the real sensory and motor events and synthesize ... |
Title: Logical Algorithms meets CHR: A meta-complexity result for Constraint Handling Rules with rule priorities |
Abstract: This paper investigates the relationship between the Logical Algorithms language (LA) of Ganzinger and McAllester and Constraint Handling Rules (CHR). We present a translation schema from LA to CHR-rp: CHR with rule priorities, and show that the meta-complexity theorem for LA can be applied to a subset of CHR... |
Title: N-norm and N-conorm in Neutrosophic Logic and Set, and the Neutrosophic Topologies |
Abstract: In this paper we present the N-norms/N-conorms in neutrosophic logic and set as extensions of T-norms/T-conorms in fuzzy logic and set. Also, as an extension of the Intuitionistic Fuzzy Topology we present the Neutrosophic Topologies. |
Title: Differential Privacy with Compression |
Abstract: This work studies formal utility and privacy guarantees for a simple multiplicative database transformation, where the data are compressed by a random linear or affine transformation, reducing the number of data records substantially, while preserving the number of original input variables. We provide an anal... |
Title: A cautionary tale on the efficiency of some adaptive Monte Carlo schemes |
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