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Title: Ontology-based inference for causal explanation |
Abstract: We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of forma... |
Title: Punctuation effects in English and Esperanto texts |
Abstract: A statistical physics study of punctuation effects on sentence lengths is presented for written texts: \it Alice in wonderland and \it Through a looking glass. The translation of the first text into esperanto is also considered as a test for the role of punctuation in defining a style, and for contrasting nat... |
Title: Polynomial Learning of Distribution Families |
Abstract: The question of polynomial learnability of probability distributions, particularly Gaussian mixture distributions, has recently received significant attention in theoretical computer science and machine learning. However, despite major progress, the general question of polynomial learnability of Gaussian mixt... |
Title: Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection |
Abstract: Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of selected portfolios among a vast pool of assets, as demonstrated in Fan et al (2008). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. ... |
Title: Many-to-Many Graph Matching: a Continuous Relaxation Approach |
Abstract: Graphs provide an efficient tool for object representation in various computer vision applications. Once graph-based representations are constructed, an important question is how to compare graphs. This problem is often formulated as a graph matching problem where one seeks a mapping between vertices of two g... |
Title: Supervised classification for a family of Gaussian functional models |
Abstract: In the framework of supervised classification (discrimination) for functional data, it is shown that the optimal classification rule can be explicitly obtained for a class of Gaussian processes with "triangular" covariance functions. This explicit knowledge has two practical consequences. First, the consisten... |
Title: Dimensions of Formality: A Case Study for MKM in Software Engineering |
Abstract: We study the formalization of a collection of documents created for a Software Engineering project from an MKM perspective. We analyze how document and collection markup formats can cope with an open-ended, multi-dimensional space of primary and secondary classifications and relationships. We show that RDFa-b... |
Title: Evidence and Evolution: A Review |
Abstract: "Evidence and Evolution: the Logic behind the Science" was published in 2008 by Elliott Sober. It examines the philosophical foundations of the statistical arguments used to evaluate hypotheses in evolutionary biology, based on simple examples and likelihood ratios. The difficulty with reading the book from a... |
Title: Variance Estimation Using Refitted Cross-validation in Ultrahigh Dimensional Regression |
Abstract: Variance estimation is a fundamental problem in statistical modeling. In ultrahigh dimensional linear regressions where the dimensionality is much larger than sample size, traditional variance estimation techniques are not applicable. Recent advances on variable selection in ultrahigh dimensional linear regre... |
Title: Clustering processes |
Abstract: The problem of clustering is considered, for the case when each data point is a sample generated by a stationary ergodic process. We propose a very natural asymptotic notion of consistency, and show that simple consistent algorithms exist, under most general non-parametric assumptions. The notion of consisten... |
Title: System Dynamics Modelling of the Processes Involving the Maintenance of the Naive T Cell Repertoire |
Abstract: The study of immune system aging, i.e. immunosenescence, is a relatively new research topic. It deals with understanding the processes of immunodegradation that indicate signs of functionality loss possibly leading to death. Even though it is not possible to prevent immunosenescence, there is great benefit in... |
Title: The Application of a Dendritic Cell Algorithm to a Robotic Classifier |
Abstract: The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migrati... |
Title: Multifractal Network Generator |
Abstract: We introduce a new approach to constructing networks with realistic features. Our method, in spite of its conceptual simplicity (it has only two parameters) is capable of generating a wide variety of network types with prescribed statistical properties, e.g., with degree- or clustering coefficient distributio... |
Title: Optimism in Reinforcement Learning and Kullback-Leibler Divergence |
Abstract: We consider model-based reinforcement learning in finite Markov De- cision Processes (MDPs), focussing on so-called optimistic strategies. In MDPs, optimism can be implemented by carrying out extended value it- erations under a constraint of consistency with the estimated model tran- sition probabilities. The... |
Title: Sparse Linear Identifiable Multivariate Modeling |
Abstract: In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully Bayesian hier... |
Title: Spatial clustering of array CGH features in combination with hierarchical multiple testing |
Abstract: We propose a new approach for clustering DNA features using array CGH data from multiple tumor samples. We distinguish data-collapsing: joining contiguous DNA clones or probes with extremely similar data into regions, from clustering: joining contiguous, correlated regions based on a maximum likelihood princi... |
Title: Compressed Sensing with off-axis frequency-shifting holography |
Abstract: This work reveals an experimental microscopy acquisition scheme successfully combining Compressed Sensing (CS) and digital holography in off-axis and frequency-shifting conditions. CS is a recent data acquisition theory involving signal reconstruction from randomly undersampled measurements, exploiting the fa... |
Title: Designing neural networks that process mean values of random variables |
Abstract: We introduce a class of neural networks derived from probabilistic models in the form of Bayesian networks. By imposing additional assumptions about the nature of the probabilistic models represented in the networks, we derive neural networks with standard dynamics that require no training to determine the sy... |
Title: Adjusting for Network Size and Composition Effects in Exponential-Family Random Graph Models |
Abstract: Exponential-family random graph models (ERGMs) provide a principled way to model and simulate features common in human social networks, such as propensities for homophily and friend-of-a-friend triad closure. We show that, without adjustment, ERGMs preserve density as network size increases. Density invarianc... |
Title: Query strategy for sequential ontology debugging |
Abstract: Debugging of ontologies is an important prerequisite for their wide-spread application, especially in areas that rely upon everyday users to create and maintain knowledge bases, as in the case of the Semantic Web. Recent approaches use diagnosis methods to identify causes of inconsistent or incoherent ontolog... |
Title: Isometric Embeddings in Imaging and Vision: Facts and Fiction |
Abstract: We explore the practicability of Nash's Embedding Theorem in vision and imaging sciences. In particular, we investigate the relevance of a result of Burago and Zalgaller regarding the existence of isometric embeddings of polyhedral surfaces in $^3$ and we show that their proof does not extended directly to hi... |
Title: Approximation for a Toy Defective Ising Model |
Abstract: It has been previously shown that one can use the ME methodology (Caticha Giffin 2006) to reproduce a mean field solution for a simple fluid (Tseng 2004). One could easily use the case of a simple ferromagnetic material as well. The drawback to the mean field approach is that one must assume that all atoms mu... |
Title: Graphic Symbol Recognition using Graph Based Signature and Bayesian Network Classifier |
Abstract: We present a new approach for recognition of complex graphic symbols in technical documents. Graphic symbol recognition is a well known challenge in the field of document image analysis and is at heart of most graphic recognition systems. Our method uses structural approach for symbol representation and stati... |
Title: Employing fuzzy intervals and loop-based methodology for designing structural signature: an application to symbol recognition |
Abstract: Motivation of our work is to present a new methodology for symbol recognition. We support structural methods for representing visual associations in graphic documents. The proposed method employs a structural approach for symbol representation and a statistical classifier for recognition. We vectorize a graph... |
Title: Multiple-Relaxation-Time Lattice Boltzmann Approach to Compressible Flows with Flexible Specific-Heat Ratio and Prandtl Number |
Abstract: A new multiple-relaxation-time lattice Boltzmann scheme for compressible flows with arbitrary specific heat ratio and Prandtl number is presented. In the new scheme, which is based on a two-dimensional 16-discrete-velocity model, the moment space and the corresponding transformation matrix are constructed acc... |
Title: Simple Type Theory as Framework for Combining Logics |
Abstract: Simple type theory is suited as framework for combining classical and non-classical logics. This claim is based on the observation that various prominent logics, including (quantified) multimodal logics and intuitionistic logics, can be elegantly embedded in simple type theory. Furthermore, simple type theory... |
Title: Bayesian estimation of regularization and PSF parameters for Wiener-Hunt deconvolution |
Abstract: This paper tackles the problem of image deconvolution with joint estimation of PSF parameters and hyperparameters. Within a Bayesian framework, the solution is inferred via a global a posteriori law for unknown parameters and object. The estimate is chosen as the posterior mean, numerically calculated by mean... |
Title: Learning from Multiple Outlooks |
Abstract: We propose a novel problem formulation of learning a single task when the data are provided in different feature spaces. Each such space is called an outlook, and is assumed to contain both labeled and unlabeled data. The objective is to take advantage of the data from all the outlooks to better classify each... |
Title: A Geometric View of Conjugate Priors |
Abstract: In Bayesian machine learning, conjugate priors are popular, mostly due to mathematical convenience. In this paper, we show that there are deeper reasons for choosing a conjugate prior. Specifically, we formulate the conjugate prior in the form of Bregman divergence and show that it is the inherent geometry of... |
Title: Large Margin Multiclass Gaussian Classification with Differential Privacy |
Abstract: As increasing amounts of sensitive personal information is aggregated into data repositories, it has become important to develop mechanisms for processing the data without revealing information about individual data instances. The differential privacy model provides a framework for the development and theoret... |
Title: Perturbation Resilience and Superiorization of Iterative Algorithms |
Abstract: Iterative algorithms aimed at solving some problems are discussed. For certain problems, such as finding a common point in the intersection of a finite number of convex sets, there often exist iterative algorithms that impose very little demand on computer resources. For other problems, such as finding that p... |
Title: Distributive Stochastic Learning for Delay-Optimal OFDMA Power and Subband Allocation |
Abstract: In this paper, we consider the distributive queue-aware power and subband allocation design for a delay-optimal OFDMA uplink system with one base station, $K$ users and $N_F$ independent subbands. Each mobile has an uplink queue with heterogeneous packet arrivals and delay requirements. We model the problem a... |
Title: Electronic Geometry Textbook: A Geometric Textbook Knowledge Management System |
Abstract: Electronic Geometry Textbook is a knowledge management system that manages geometric textbook knowledge to enable users to construct and share dynamic geometry textbooks interactively and efficiently. Based on a knowledge base organizing and storing the knowledge represented in specific languages, the system ... |
Title: The Exact Closest String Problem as a Constraint Satisfaction Problem |
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