Theory and Algorithms Commons^™

Snap-And-Ask: Answering Multimodal Question By Naming Visual Instance, Wei Zhang, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

In real-life, it is easier to provide a visual cue when asking a question about a possibly unfamiliar topic, for example, asking the question, “Where was this crop circle found?”. Providing an image of the instance is far more convenient than texting a verbose description of the visual properties, especially when the name of the query instance is not known. Nevertheless, having to identify the visual instance before processing the question and eventually returning the answer makes multimodal question-answering technically challenging. This paper addresses the problem of visual-totext naming through the paradigm of answering-by-search in a two-stage computational framework, which …

Microblog Search And Filtering With Time Sensitive Feedback And Thresholding Based On Bm25, Wei Gao, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Microblogs such as Twitter are considered faster first-hand sources of information with many real-time fashions. We report our work in the real-time adhoc search and filtering tasks of TREC 2012 microblog track. Our system is built based on the traditional BM25 relevance model, in which specific techniques are tried out to respond to the ne.ed of frnding relevant tweets, ln thc real-time adhoc task, we applied a peak detection algorithm for the process of blind feedback, We also tried to automatically combine the search results of multiple retrieval techniques. In the real-time filtering pilot task, we examine the effectiveness of …

Verification Of Graph Programs, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

GP (for Graph Programs) is an experimental nondeterministic programming language which allows for the manipulation of graphs at a high level of abstraction. The program states of GP are directed labelled graphs. These are manipulated directly via the application of (conditional) rule schemata, which generalise double-pushout rules with expressions over labels and relabelling. In contrast with graph grammars, the application of these rule schemata is directed by a number of simple control constructs including sequential composition, conditionals, and as-long-as-possible iteration. GP shields programmers at all times from low-level implementation issues (e.g. graph representation), and with its nondeterministic semantics, allows one …

Verifying Total Correctness Of Graph Programs, Christopher M. Poskitt, Detlef Plump

Research Collection School Of Computing and Information Systems

GP 2 is an experimental nondeterministic programming language based on graph transformation rules, allowing for visual programming and the solving of graph problems at a high-level of abstraction. In previous work we demonstrated how to verify graph programs using a Hoare-style proof calculus, but only partial correctness was considered. In this paper, we add new proof rules and termination functions, which allow for proofs to additionally guarantee that program executions always terminate (weak total correctness), or that programs always terminate and do so without failure (total correctness). We show that the new proof rules are sound with respect to the …

Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

For over two decades, satellite sensors have provided the locations of global fire activity with ever-increasing accuracy. However, the ability to measure fire intensity, know as fire radiative power (FRP), and its potential relationships to meteorology and smoke plume injection heights, are currently limited by the pixel resolution. This dissertation describes the development of a new, sub-pixel-based FRP calculation (FRP_f) for fire pixels detected by the MODerate Resolution Imaging Spectroradiometer (MODIS) fire detection algorithm (Collection 5), which is subsequently applied to several large wildfire events in North America. The methodology inherits an earlier bi-spectral algorithm for retrieving sub-pixel …

Theoretical Approaches To The Characterization Of Water, Aqueous Interfaces, And Improved Sampling Of Protein Conformational Changes, Alexis J. Lee

LSU New Orleans Theses and Dissertations

Methods to advance the understanding of water and other aqueous systems are devel- oped. This work falls into three areas: The creation of better interaction potentials for water, improved methods for sampling configurational space, and the applications of these methods to understand systems of interest. Charge transfer has been shown by ab initio methods to be important in the water–water and water–ion interactions. A model for treating charge transfer in liquid water and aqueous systems is presented in this manuscript. The model is called Discrete Charge Transfer (DCT) and is based on the commonly-used TIP4P/2005 model, which represents the charge …

Measurement-Driven Performance Analysis Of Indoor Femtocellular Networks, Trung-Tuan Luong, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan

Research Collection School Of Computing and Information Systems

This paper describes initial empirical studies, performed on a 6-node 3G indoor femtocellular testbed, that investigate the impact of pedestrian mobility on network parameters, such as handoff behavior and data throughput. The studies establish that, owing to the small radii of cells, even modest changes in movement speed can have disproportionately large impact on handoff patterns and network throughput. By also revealing a strong temporal dependency effect, the studies motivate the need for algorithms to accurately predict RF signal strength distributions in dynamic indoor environments. We present such an RF prediction algorithm, based on crowd-sourced signal strength readings, and show …

Degree Constrained Triangulation, Roshan Gyawali

UNLV Theses, Dissertations, Professional Papers, and Capstones

Triangulation of simple polygons or sets of points in two dimensions is a widely investigated problem in computational geometry. Some researchers have considered variations of triangulation problems that include minimum weight triangulation, de-launay triangulation and triangulation refinement. In this thesis we consider a constrained version of the triangulation problem that asks for triangulating a given domain (polygon or point sites) so that the resulting triangulation has an increased number of even degree vertices. This problem is called Degree Constrained Triangulation (DCT). We propose four algorithms to solve DCT problems. We also present experimental results based on the implementation of the …

Message Passing Algorithm For Different Problems Sum, Mean, Guide And Sorting In A Rooted Tree Network., Sabaresh Nageswara Rao Maddula

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis, we give message passing algorithms in distributed environment for five different problems of a rooted tree having n nodes. In the first algorithm, every node has a value; the root calculates the sum of those values, and sends it to all the nodes in the network. In the second algorithm, the root computes the value of mean of values of all the nodes, and sends it to all nodes of the network. The third algorithm calculates the guide pairs. Guide pair of a node x is an ordered pair (pre_index(x), post_index(x)), where pre_index(x) and post_index(x) are the …

Transition States Of Dbt Molecule At The Mos2/Co9s8 Interface: First Principles, Svetlana Gelpi, Alvaro S. Laham, Gilles Berhault, Brenda Torres, Russel R. Chianelli, Manuel Ramos *

COURI Symposium Abstracts, Summer 2012

Sulfur removal in crude oil, is one of most important application when designing catalytic material to target hydrodesulphurization reactions. This particular study comprehends the quantum computational calculations for the transitional states during the HDS reaction in the molecular model of MoS₂/Co₉S₈, which is a theoretical molecular model to describe the synergic contact between both crystallographic structures. Results produced using the exchange correlation Perdew-Burke-Ernzerhof(PBE) functional indicate the existence of endothermic and exothermic transitions during the attachment of DBT molecules. In addition, it proves that promotion (addition of Co, Ni) provokes the electronic configuration of electron …

On-Line Portfolio Selection With Moving Average Reversion, Bin Li, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

On-line portfolio selection has attracted increasing interests in machine learning and AI communities recently. Empirical evidences show that stock's high and low prices are temporary and stock price relatives are likely to follow the mean reversion phenomenon. While the existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied in some real datasets, leading to poor performance when the assumption does not hold. To overcome the limitation, this article proposes a multiple-period mean reversion, or so-called Moving Average Reversion (MAR), and a …

Exact Soft Confidence-Weighted Learning, Jialei Wang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we propose a new Soft Confidence-Weighted (SCW) online learning scheme, which enables the conventional confidence-weighted learning method to handle non-separable cases. Unlike the previous confidence-weighted learning algorithms, the proposed soft confidence-weighted learning method enjoys all the four salient properties: (i) large margin training, (ii) confidence weighting, (iii) capability to handle non-separable data, and (iv) adaptive margin. Our experimental results show that the proposed SCW algorithms significantly outperform the original CW algorithm. When comparing with a variety of state-of-the art algorithms (including AROW, NAROW and NHERD), we found that SCW generally achieves better or at least comparable predictive …

Fast Bounded Online Gradient Descent Algorithms For Scalable Kernel-Based Online Learning, Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Kernel-based online learning has often shown state-of-the-art performance for many online learning tasks. It, however, suffers from a major shortcoming, that is, the unbounded number of support vectors, making it non-scalable and unsuitable for applications with large-scale datasets. In this work, we study the problem of bounded kernel-based online learning that aims to constrain the number of support vectors by a predefined budget. Although several algorithms have been proposed in literature, they are neither computationally efficient due to their intensive budget maintenance strategy nor effective due to the use of simple Perceptron algorithm. To overcome these limitations, we propose a …

Online Kernel Selection: Algorithms And Evaluations, Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being used, identifying good kernels among a set of given kernels is important to the success of kernel methods. A straightforward approach to address this problem is cross-validation by training a separate classifier for each kernel and choosing the best kernel classifier out of them. Another approach is Multiple Kernel Learning (MKL), which aims to learn a single kernel classifier from an optimal combination of multiple kernels. However, both approaches suffer from a high computational …

A Multi-Paradigm Modeling Framework For Modeling And Simulating Problem Situations, Christopher James Lynch

Computational Modeling & Simulation Engineering Theses & Dissertations

Problem situations are problems whose specifications are not universally agreed upon making them a challenge to be modeled and simulated. Models of problem situations depart from the premise of well-defined problems, problems where stakeholders disagree, but also modelers' interpretations play a role in their design and computer implementation.

This thesis proposes a multi-paradigm modeling framework for modeling and simulating problem situations in order to explore the problem space of the problem situations and answer specific modeling questions.

The proposed framework implements the Modeling and Simulation (M&S) System Development Framework (MS-SDF), which is a methodology for modeling a problem situation while …

Lagrangian Relaxation For Large-Scale Multi-Agent Planning, Geoffrey J. Gordon, Pradeep Varakantham, William Yeoh, Hoong Chuin Lau, Ajay Srinivasan Aravamudhan, Shih-Fen Cheng

LARC Research Publications

Multi-agent planning is a well-studied problem with applications in various areas. Due to computational constraints, existing research typically focuses either on unstructured domains with many agents, where we are content with heuristic solutions, or domains with small numbers of agents or special structure, where we can find provably near-optimal solutions. In contrast, here we focus on provably near-optimal solutions in domains with many agents, by exploiting influence limit. To that end, we make two key contributions: (a) an algorithm, based on Lagrangian relaxation and randomized rounding, for solving multi-agent planning problems represented as large mixed-integer programs; (b) a proof of …

The Intersection Between Science And Computer Science Is Almost Empty, Dick Hamlet

Systems Science Friday Noon Seminar Series

Traditionally, a science such as physics overlaps with mathematics and engineering in a way that has been astonishingly productive. The math provides precise expression for the science, which in turn supplies the engineering with the information it needs to exploit physical phenomena. Computer science naturally wishes to put itself in the center of the traditional picture as a science. Unfortunately, it won't wash. The `science' of programming is pure and simple mathematics, not science. The distinction is more than linguistic, since science and mathematics have quite distinct goals and methods. By making the wrong choice, computer science research has been …

An Evolutionary Search Paradigm That Learns With Past Experiences, Liang Feng, Yew-Soon Ong, Ivor Tsang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

A major drawback of evolutionary optimization approaches in the literature is the apparent lack of automated knowledge transfers and reuse across problems. Particularly, evolutionary optimization methods generally start a search from scratch or ground zero state, independent of how similar the given new problem of interest is to those optimized previously. In this paper, we present a study on the transfer of knowledge in the form of useful structured knowledge or latent patterns that are captured from previous experiences of problem-solving to enhance future evolutionary search. The essential contributions of our present study include the meme learning and meme selection …

Distributed Incomplete Pattern Matching Via A Novelweighted Bloom Filter, Siyuan Liu, Lei Kang, Lei Chen, Lionel Ni

Research Collection School Of Computing and Information Systems

In this paper, we first propose a very interesting and practical problem, pattern matching in a distributed mobile environment. Pattern matching is a well-known problem and extensive research has been conducted for performing effective and efficient search. However, previous proposed approaches assume that data are centrally stored, which is not the case in a mobile environment (e.g., mobile phone networks), where one person’s pattern could be separately stored in a number of different stations, and such a local pattern is incomplete compared with the global pattern. A simple solution to pattern matching over a mobile environment is to collect all …

Utilization Of Probabilistic Models In Short Read Assembly From Second-Generation Sequencing, Matthew W. Segar

Honors Theses

With the advent of cheaper and faster DNA sequencing technologies, assembly methods have greatly changed. Instead of outputting reads that are thousands of base pairs long, new sequencers parallelize the task by producing read lengths between 35 and 400 base pairs. Reconstructing an organism’s genome from these millions of reads is a computationally expensive task. Our algorithm solves this problem by organizing and indexing the reads using n-grams, which are short, fixed-length DNA sequences of length n. These n-grams are used to efficiently locate putative read joins, thereby eliminating the need to perform an exhaustive search over all possible read …