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Abstract: The shift from industrial economy to knowledge economy in today's world has revolutionalized strategic planning in organizations as well as their problem solving approaches. The point of focus today is knowledge and service production with more emphasis been laid on knowledge capital. Many organizations are i... |
Title: Curve Reconstruction in Riemannian Manifolds: Ordering Motion Frames |
Abstract: In this article we extend the computational geometric curve reconstruction approach to curves in Riemannian manifolds. We prove that the minimal spanning tree, given a sufficiently dense sample, correctly reconstructs the smooth arcs and further closed and simple curves in Riemannian manifolds. The proof is b... |
Title: Translating biomarkers between multi-way time-series experiments |
Abstract: Translating potential disease biomarkers between multi-species 'omics' experiments is a new direction in biomedical research. The existing methods are limited to simple experimental setups such as basic healthy-diseased comparisons. Most of these methods also require an a priori matching of the variables (e.g... |
Title: Descriptive-complexity based distance for fuzzy sets |
Abstract: A new distance function dist(A,B) for fuzzy sets A and B is introduced. It is based on the descriptive complexity, i.e., the number of bits (on average) that are needed to describe an element in the symmetric difference of the two sets. The distance gives the amount of additional information needed to describ... |
Title: Adaptive Parallel Tempering for Stochastic Maximum Likelihood Learning of RBMs |
Abstract: Restricted Boltzmann Machines (RBM) have attracted a lot of attention of late, as one the principle building blocks of deep networks. Training RBMs remains problematic however, because of the intractibility of their partition function. The maximum likelihood gradient requires a very robust sampler which can a... |
Title: Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference |
Abstract: We propose a novel algorithm to solve the expectation propagation relaxation of Bayesian inference for continuous-variable graphical models. In contrast to most previous algorithms, our method is provably convergent. By marrying convergent EP ideas from (Opper&Winther 05) with covariance decoupling techniques... |
Title: Adaptive Cluster Expansion (ACE): A Multilayer Network for Estimating Probability Density Functions |
Abstract: We derive an adaptive hierarchical method of estimating high dimensional probability density functions. We call this method of density estimation the "adaptive cluster expansion" or ACE for short. We present an application of this approach, based on a multilayer topographic mapping network, that adaptively es... |
Title: Analysis of Agglomerative Clustering |
Abstract: The diameter $k$-clustering problem is the problem of partitioning a finite subset of $^d$ into $k$ subsets called clusters such that the maximum diameter of the clusters is minimized. One early clustering algorithm that computes a hierarchy of approximate solutions to this problem (for all values of $k$) is ... |
Title: Stochastic Vector Quantisers |
Abstract: In this paper a stochastic generalisation of the standard Linde-Buzo-Gray (LBG) approach to vector quantiser (VQ) design is presented, in which the encoder is implemented as the sampling of a vector of code indices from a probability distribution derived from the input vector, and the decoder is implemented a... |
Title: The Development of Dominance Stripes and Orientation Maps in a Self-Organising Visual Cortex Network (VICON) |
Abstract: A self-organising neural network is presented that is based on a rigorous Bayesian analysis of the information contained in individual neural firing events. This leads to a visual cortex network (VICON) that has many of the properties emerge when a mammalian visual cortex is exposed to data arriving from two ... |
Title: Dos and don'ts of reduced chi-squared |
Abstract: Reduced chi-squared is a very popular method for model assessment, model comparison, convergence diagnostic, and error estimation in astronomy. In this manuscript, we discuss the pitfalls involved in using reduced chi-squared. There are two independent problems: (a) The number of degrees of freedom can only b... |
Title: Exact sampling for intractable probability distributions via a Bernoulli factory |
Abstract: Many applications in the field of statistics require Markov chain Monte Carlo methods. Determining appropriate starting values and run lengths can be both analytically and empirically challenging. A desire to overcome these problems has led to the development of exact, or perfect, sampling algorithms which co... |
Title: Estimating Networks With Jumps |
Abstract: We study the problem of estimating a temporally varying coefficient and varying structure (VCVS) graphical model underlying nonstationary time series data, such as social states of interacting individuals or microarray expression profiles of gene networks, as opposed to i.i.d. data from an invariant model wid... |
Title: Detecting Image Forgeries using Geometric Cues |
Abstract: This chapter presents a framework for detecting fake regions by using various methods including watermarking technique and blind approaches. In particular, we describe current categories on blind approaches which can be divided into five: pixel-based techniques, format-based techniques, camera-based technique... |
Title: Non-Parametric Maximum Likelihood Density Estimation and Simulation-Based Minimum Distance Estimators |
Abstract: Indirect inference estimators (i.e., simulation-based minimum distance estimators) in a parametric model that are based on auxiliary non-parametric maximum likelihood density estimators are shown to be asymptotically normal. If the parametric model is correctly specified, it is furthermore shown that the asym... |
Title: On the CNF encoding of cardinality constraints and beyond |
Abstract: In this report, we propose a quick survey of the currently known techniques for encoding a Boolean cardinality constraint into a CNF formula, and we discuss about the relevance of these encodings. We also propose models to facilitate analysis and design of CNF encodings for Boolean constraints. |
Title: Queue-Aware Dynamic Clustering and Power Allocation for Network MIMO Systems via Distributive Stochastic Learning |
Abstract: In this paper, we propose a two-timescale delay-optimal dynamic clustering and power allocation design for downlink network MIMO systems. The dynamic clustering control is adaptive to the global queue state information (GQSI) only and computed at the base station controller (BSC) over a longer time scale. On ... |
Title: Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: A Sure Screening Approach |
Abstract: We propose a novel application of the Simultaneous Orthogonal Matching Pursuit (S-OMP) procedure for sparsistant variable selection in ultra-high dimensional multi-task regression problems. Screening of variables, as introduced in , is an efficient and highly scalable way to remove many irrelevant variables f... |
Title: Interpolation in Equilibrium Logic and Answer Set Programming: the Propositional Case |
Abstract: Interpolation is an important property of classical and many non classical logics that has been shown to have interesting applications in computer science and AI. Here we study the Interpolation Property for the propositional version of the non-monotonic system of equilibrium logic, establishing weaker or str... |
Title: Diffusion-geometric maximally stable component detection in deformable shapes |
Abstract: Maximally stable component detection is a very popular method for feature analysis in images, mainly due to its low computation cost and high repeatability. With the recent advance of feature-based methods in geometric shape analysis, there is significant interest in finding analogous approaches in the 3D wor... |
Title: Artificial Intelligence in Reverse Supply Chain Management: The State of the Art |
Abstract: Product take-back legislation forces manufacturers to bear the costs of collection and disposal of products that have reached the end of their useful lives. In order to reduce these costs, manufacturers can consider reuse, remanufacturing and/or recycling of components as an alternative to disposal. The imple... |
Title: Survey & Experiment: Towards the Learning Accuracy |
Abstract: To attain the best learning accuracy, people move on with difficulties and frustrations. Though one can optimize the empirical objective using a given set of samples, its generalization ability to the entire sample distribution remains questionable. Even if a fair generalization guarantee is offered, one stil... |
Title: Type I error rate control for testing many hypotheses: a survey with proofs |
Abstract: This paper presents a survey on some recent advances for the type I error rate control in multiple testing methodology. We consider the problem of controlling the $k$-family-wise error rate (kFWER, probability to make $k$ false discoveries or more) and the false discovery proportion (FDP, proportion of false ... |
Title: lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers |
Abstract: We assume data sampled from a mixture of d-dimensional linear subspaces with spherically symmetric distributions within each subspace and an additional outlier component with spherically symmetric distribution within the ambient space (for simplicity we may assume that all distributions are uniform on their c... |
Title: Self-Organising Stochastic Encoders |
Abstract: The processing of mega-dimensional data, such as images, scales linearly with image size only if fixed size processing windows are used. It would be very useful to be able to automate the process of sizing and interconnecting the processing windows. A stochastic encoder that is an extension of the standard Li... |
Title: A Self-Organising Neural Network for Processing Data from Multiple Sensors |
Abstract: This paper shows how a folded Markov chain network can be applied to the problem of processing data from multiple sensors, with an emphasis on the special case of 2 sensors. It is necessary to design the network so that it can transform a high dimensional input vector into a posterior probability, for which p... |
Title: Exploring the Consequences of IED Deployment with a Generalized Linear Model Implementation of the Canadian Traveller Problem |
Abstract: The deployment of improvised explosive devices (IEDs) along major roadways has been a favoured strategy of insurgents in recent war zones, both for the ability to cause damage to targets along roadways at minimal cost, but also as a means of controlling the flow of traffic and causing additional expense to op... |
Title: Empirical estimation of entropy functionals with confidence |
Abstract: This paper introduces a class of k-nearest neighbor ($k$-NN) estimators called bipartite plug-in (BPI) estimators for estimating integrals of non-linear functions of a probability density, such as Shannon entropy and R\'enyi entropy. The density is assumed to be smooth, have bounded support, and be uniformly ... |
Title: Travel Time Estimation Using Floating Car Data |
Abstract: This report explores the use of machine learning techniques to accurately predict travel times in city streets and highways using floating car data (location information of user vehicles on a road network). The aim of this report is twofold, first we present a general architecture of solving this problem, the... |
Title: Robust rank correlation based screening |
Abstract: Independence screening is a variable selection method that uses a ranking criterion to select significant variables, particularly for statistical models with nonpolynomial dimensionality or "large p, small n" paradigms when p can be as large as an exponential of the sample size n. In this paper we propose a r... |
Title: Using virtual human for an interactive customer-oriented constrained environment design |
Abstract: For industrial product design, it is very important to take into account assembly/disassembly and maintenance operations during the conceptual and prototype design stage. For these operations or other similar operations in a constrained environment, trajectory planning is always a critical and difficult issue... |
Title: Control of the False Discovery Rate Under Arbitrary Covariance Dependence |
Abstract: Multiple hypothesis testing is a fundamental problem in high dimensional inference, with wide applications in many scientific fields. In genome-wide association studies, tens of thousands of tests are performed simultaneously to find if any genes are associated with some traits and those tests are correlated.... |
Title: Extension of Dirac's chord method to the case of a nonconvex set by use of quasi-probability distributions |
Abstract: The Dirac's chord method may be suitable in different areas of physics for the representation of certain six-dimensional integrals for a convex body using the probability density of the chord length distribution. For a homogeneous model with a nonconvex body inside a medium with identical properties an analog... |
Title: Characterizing Structure Through Shape Matching and Applications to Self Assembly |
Abstract: Structural quantities such as order parameters and correlation functions are often employed to gain insight into the physical behavior and properties of condensed matter systems. While standard quantities for characterizing structure exist, often they are insufficient for treating problems in the emerging fie... |
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