NONPARAMETRIC BAYESIAN CLASSIFICATION WITH MASSIVE DATASETS: LARGE-SCALE QUASAR DISCOVERY (2009)
Alexander Gray, Gordon Richards, Robert Nichol, Robert Brunner, Andrew Moore
The kernel discriminant (a nonparametric Bayesian classifier) is appropriate for many scientific tasks because it is highly accurate (it approaches Bayes optimality as you get more data),...
Andrew Moore, Justin Boyan, Vince Cicirello, A B ∨c, A C ∨e
parking lot layout, product design, aero-dynamic design, “Million Queens ” problem, radiotherapy treatment planning, (2000 variables, 8500 clauses) Informal characterization These are problems in...
T-Cube: Quick Response to Ad-Hoc Time Series Queries against Large Datasets (2009)
Maheshkumar Sabhnani, Artur Dubrawski, Andrew Moore
Abstract. We present a novel data structure called T-Cube which dramatically improves response time to ad-hoc time series queries against large datasets. We have tested T-Cube on both synthetic and...
Mild Mania and Well-Being (2009)
Philosophy, Psychiatry, & Psychology - Volume 1, Number 3, September 1994
Not refereed. Abstract only.
Hamed Haddadi, Gianluca Iannaccone, Andrew Moore, Richard Mortier, Miguel Rio
Abstract—Accurate measurement, inference and modelling techniques are fundamental to Internet topology research. Spatial analysis of the Internet is needed to develop network planning, optimal...
Dissertation: A Statistical Framework for Spatial Comparative Genomics (2008)
Rose Hoberman, Advisor Dannie Durand, Committee Jeffrey Lawrence, Andrew Moore, David Sankoff, Russell Schwartz, ...
Thesis: A statistical framework for analyzing the spatial organization of genes within and across genomes. Applications include reconstruction of ancestral gene order, analysis
Method Time-weighted averaging (2008)
Bill Hogan, Andrew Moore, Robin Sabhnani, Rich Tsui, Mike Wagner, Weng-keen Wong, ...
Tutorial slides by Andrew Moore Note to other teachers and users of these slides. Andrew would be delighted if you found this source material useful in giving your own lectures. Feel free to use...
† Intel Research Cambridge, UK The CoMo White Paper (2008)
Gianluca Iannaccone, Christophe Diot, Derek Mcauley, Andrew Moore, Ian Pratt, Luigi Rizzo
Abstract — CoMo (Continuous Monitoring) is a passive monitoring system. CoMo has been designed to be the basic building block of an open network monitoring infrastructure that would allow...
© 2003 The New York Academy of Medicine WSARE: What’s Strange About Recent Events? (2008)
Weng-keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner
ABSTRACT This article presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques...
Jeremy Kubica, Dr. Andrew Moore
My primary research interests are machine learning, data mining, and efficient large-scale scientific and statistical com-putation. I am interested in the development of new techniques and efficient...
This paper presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly...
Weng-keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner, Dale Schuurmans
Traditional biosurveillance algorithms detect disease outbreaks by looking for peaks in a univariate time series of health-care data. Current health-care surveillance data, however, are no longer...
Abstract Bayesian Networks for Lossless Dataset Compression (2008)
The recent explosion in research on probabilistic data mining algorithms such as Bayesian networks has been focussed primarily on their use in diagnostics, prediction and efficient inference. In this...
Previous Approaches and Our Contribution (2008)
Kernel summations using the Gaussian kernel K(||xq − xr||) = e −||xq−xr| | 2 2h 2 with bandwidth h are common in many machine learning methods and physics problems. Given a set of reference...
The VLDB Journal manuscript No. (will be inserted by the editor) (2008)
Abstract We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other uses. Given...
Abstract Distributed Value Functions (2008)
Je Schneider, Weng-keen Wong, Andrew Moore, Martin Riedmiller
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learning (RL), also have properties that make distributed solutions...
Jeremy Kubica, Robert Jedicke, Joseph Masiero, Andrew Moore, Andrew Connolly
In this paper we consider the problem of finding sets of points that conform to a given underlying model from within a dense, noisy set of observations. This problem is motivated by the task of...
The Sensor Sleeve: Sensing Affective Gestures (2008)
Cliff Randell Ian, Ian Anderson, Henk Muller, Andrew Moore, Sharon Baurley
We describe the use of textile sensors mounted in a garment sleeve to detect affective gestures. The ` Sensor Sleeve' is part of a larger project to explore the role of affect in communications....
R.I.T. news and events January 15, 2009 (2008)
Dube, Will, Cometa, Michelle, Lividas, Greg, Moore, Andrew, Saffran, Mike, Downs, Kelly, ...
Graduate Council's Letter of Approval for the Proposed Revisions to the MS in Finance Program (2008)
The JMCIS Information Flow Improvement (JIFI) Assurance Strategy (2007)
Model of Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 4 Architecture Overview 19 4.1 Physical Model of Operations . . . . . . . . . . . . . . . . . . . . . . . . . . ....
Implementing Workgrou Ps, Andrew Moore, Groupware-plus Limited
This paper provides the reader with an understanding of what groupware is, how it may be used and the implications for doing so in a large organisation. Andrew Moore Technical Director Groupware-Plus...
State abstraction is of central importance in reinforcement learning and Markov decision processes. This paper studies the case of variable resolution state abstraction for continuous state...
An experimental conguration for the evaluation of CAC algorithms (2007)
Interest in Connection Admission Control (CAC) algorithms stems from the need for a network user and a network provider to forge an agreement on the Quality of Service (QoS) for a new network...
Andrew Moore, Andy Connolly, Chris Genovese, Alex Gray, Nick Kanidoris Ii, Robert Nichol, ...
Istvan Szapudi 4, and Larry Wasserman
Efficient Algorithms for Non-Parametric Clustering with Clutter (2007)
Detecting and counting overdensities in data is a common problem in the physical and geographic sciences. One of the most successful of recent algorithms for the counting version of the problem was...
John A. Peck, Andrea Mullen, Andrew Moore, Joseph H. Rumschlag
Dams decrease stream gradient and flow velocity, and often trap a stream's sediment load. For 188 years, sedimentation in the Munroe Falls dam pool on the Cuyahoga River, Ohio created a sediment...
Hierarchical Gaussian process latent variable models (2007)
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we extend the GP-LVM...
Efficient intra- and inter-night linking of asteroid detections using kd-trees (2007)
Kubica, Jeremy, Denneau, Larry, Grav, Tommy, Heasley, James, Jedicke, Robert, Masiero, Joseph, ...
The Panoramic Survey Telescope And Rapid Response System (Pan-STARRS) under development at the University of Hawaii's Institute for Astronomy is creating the first fully automated end-to-end Moving...
A Statistical Framework for Spatial Comparative Genomics (2007)
Rose Hoberman, Andrew Moore, Russell Schwartz
representing the official policies, either expressed or implied, of any sponsoring institution, or the U.S. Government.
RIT Honor Code Presentation & Honor Code (2006)
Honor Code Committee, Fagan, Annette, Macchiano, James, Moore, Andrew, Price, Mark, Provenzano, Sue, ...
PowerPoint presentation
RIT Honor Code Presentation & Honor Code (2006)
Honor Code Committee, Fagan, Annette, Macchiano, James, Moore, Andrew, Price, Mark, Provenzano, Sue, ...
PowerPoint presentation
Moore, Andrew, Ninkov, Zoran, Forrest, William
This paper is a revision of a paper presented at the SPIE Conference on Focal Plane Arrays for Space Telescopes, Aug. 2003, San Diego, California. The paper presented there appears (unrefereed) in...
Moore, Andrew, Ninkov, Zoran, Forrest, William
This paper is a revision of a paper presented at the SPIE Conference on Focal Plane Arrays for Space Telescopes, Aug. 2003, San Diego, California. The paper presented there appears (unrefereed) in...
Scalable Detection and Optimization of N-ARY Linkages (2006)
Moore, Andrew, Schneider, Jeff, Kubica, Jeremy, Goldenberg, Anna, Dubrawski, Artur, Ostlund, John, ...
Link detection and analysis has long been important in the social sciences where a single link can be the key evidence that leads an intelligence analyst to additional clues to a threat event. A...
Sequence Selection for Active Learning (2006)
Brigham Anderson, Sajid Siddiqi, Andrew Moore
Scarcity of labelled data often hampers the learning of Hidden Markov Models in applications such as speech, text, and video processing. Although current active learning algorithms can select...
Operating, testing and evaluating hybridized silicon P-I-N arrays (2005)
Use of CCD detector arrays as visible imagers in space telescopes has been problematic. Charge-coupled devices rapidly deteriorate due to damage from the high radiation environment of space....
Operating, testing and evaluating hybridized silicon P-I-N arrays (2005)
Use of CCD detector arrays as visible imagers in space telescopes has been problematic. Charge-coupled devices rapidly deteriorate due to damage from the high radiation environment of space....
Massive Science with VO and Grids (2005)
Nichol, Robert, Smith, Garry, Miller, Christopher, Freeman, Peter, Genovese, Chris, Wasserman, Larry, ...
There is a growing need for massive computational resources for the analysis of new astronomical datasets. To tackle this problem, we present here our first steps towards marrying two new and...
Discriminators for use in flow-based classification (2005)
Andrew Moore, Michael Crogan, Andrew W. Moore, Queen Mary, Denis Zuev, Denis Zuev, ...
Any assessment of classification techniques requires data. This document describes sets of data intended to aid in the assessment of classification work. A number of data sets are described; each...
Variable KD-Tree Algorithms for Efficient Spatial Pattern Search (2005)
Jeremy Kubica, Joseph Masiero, Andrew Moore, Robert Jedicke, Andrew Connolly
In this paper we consider the problem of finding sets of points that conform to a given underlying model from within a dense, noisy set of observations. This problem is motivated by the task of...
Jeremy Kubica, Andrew Moore, Andrew Connolly, Robert Jedicke
In this paper we examine the problem of spatial data association- identifying which track/observations pairs could feasibly be associated. Efficiently and accurately finding these potential...
Active learning for hidden markov models: Objective functions and algorithms (2005)
Brigham Anderson, Andrew Moore
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by closing the...
Jeremy Kubica, Andrew Moore, Andrew Connolly, Robert Jedicke
In this paper we examine the problem of spatial data association- identifying which track/observations pairs could feasibly be associated. Efficiently and accurately finding these potential...
Jeremy Kubica, Andrew Moore, Andrew Connolly, Robert Jedicke
In this paper we examine the problem of spatial data association- identifying which track/observations pairs could feasibly be associated. Efficiently and accurately finding these potential...
Variable KD-Tree Algorithms for Efficient Spatial Pattern Search (2005)
Jeremy Kubica, Joseph Masiero, Andrew Moore, Robert Jedicke, Andrew Connolly
In this paper we consider the problem of finding sets of points that conform to a given underlying model from within a dense, noisy set of observations. This problem is motivated by the task of...
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and automatic (i.e. no parameter tuning). Naive Bayes and...
Variable KD-Tree Algorithms for Efficient Spatial Pattern Search (2005)
Jeremy Kubica, Joseph Masiero, Andrew Moore, Robert Jedicke, Andrew Connolly
In this paper we consider the problem of finding sets of points that conform to a given underlying model from within a dense, noisy set of observations. This problem is motivated by the task of...
Active learning for hidden markov models: Objective functions and algorithms (2005)
Brigham Anderson, Andrew Moore
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by closing the...
Tractable learning of large bayes net structures from sparse data (2004)
statistics for creating the global Bayes Net. This paper addresses three questions. Is it useful to attempt to learn a Bayesian network structure with hundreds of thousands of nodes? How should such...
Tractable Planning Under Uncertainty: Exploiting Structure (2004)
Joelle Pineau, Matthew Mason, Andrew Moore, Michael Littman
THE problem of planning under uncertainty has received significant attention in the scientific community over the past few years. It is now well-recognized that considering uncertainty during...
3.2 Parameter Space Methods........................ 6 (2004)
Jeremy Kubica, Andrew Moore, Andrew Connolly, Robert Jedicke
In this paper we examine a fundamental problem in many tracking tasks: track initiation (also called linkage). This problem consists of taking sets of point observations from different time steps and...
High-Dimensional Probabilistic Classification For Drug Discovery (2004)
Alexander Gray, Paul Komarek, Ting Liu, Andrew Moore
Automated high-throughput drug screening constitutes a critical emerging approach in modern pharmaceutical research. The statistical task of interest is that of discriminating active versus inactive...
Structured Errors in Optical Gigabit Ethernet (2004)
Packets Laura James, Laura James, Andrew Moore, Madeleine Glick
This paper presents a study of the errors observed when an optical Gigabit Ethernet link is subject to attenuation. We use a set of purpose-built tools which allows us to examine the errors observed...
Belief State Approaches to Signaling Alarms in (2004)
Surveillance Systems Kaustav, Kaustav Das, Andrew Moore
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detection systems produce a...
Active learning for anomaly and rare-category detection (2004)
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional statistical definition...
Active learning for anomaly and rare-category detection (2004)
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional statistical definition...
Structured Errors in Optical Gigabit Ethernet (2004)
Laura James, Laura James, Andrew Moore, Andrew Moore, Madeleine Glick, Madeleine Glick
Abstract. This paper presents a study of the errors observed when an optical Gigabit Ethernet link is subject to attenuation. We use a set of purpose-built tools which allows us to examine the errors...
Spatial data structures for efficient trajectory-based queries (2004)
Jeremy Kubica, Andrew Moore, Andrew Connolly, Robert Jedicke
Spatial queries involving trajectories of moving objects are fundamental in a variety of domains. For example, we may wish to determine which points or regions to which an object passes “close. ”...
Hall, James, Moore, Andrew, Pratt, Ian, Leslie, Ian
Workshop im SoSe; Mittwoch, 25. August 2003
Hall, James, Moore, Andrew, Pratt, Ian, Leslie, Ian
Workshop im SoSe; Mittwoch, 25. August 2003
Goebel, Andreas, Moore, Andrew, Weatherall, Rosamund, Roewer, Norbert, Schedel, Robert, Sprotte, Guenter
Abstract Background We have recently reported successful treatment of patients with chronic pain syndromes using human pooled intravenous immunoglobulin (IVIG) in a prospective, open-label cohort...
Multi-protocol visualization: a tool demonstration (2003)
James Hall, Andrew Moore, Ian Pratt, Ian Leslie
This paper describes a system for the visualization of multiple protocols. The visualizer makes possible the identification of both intra and inter-protocol behaviour. This tool has become a critical...
Tractable group detection on large link data sets (2003)
Jeremy Kubica, Andrew Moore, Jeff Schneider
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, human resources, and...
Fast Logistic Regression for Data Mining, Text Classification and Link Detection (2003)
Previous work by the authors [1] demonstrated that logistic regression can be a fast and accurate data mining tool for life sciences datasets, competitive with modern tools like support vector...
Probabilistic noise identification and data cleaning (2003)
Real world data is never as perfect as we would like it to be and can often suffer from corruptions that may impact interpretations of the data, models created from the data, and decisions made based...
Architecture of a network monitor (2003)
Andrew Moore, James Hall, Christian Kreibich, Euan Harris, Ian Pratt
Abstract — This paper describes a system for simultaneously monitoring multiple protocols. It performs full linerate capture and implements on-line analysis and compression to record interesting...
Multi-protocol visualization: a tool demonstration (2003)
James Hall, Andrew Moore, Ian Pratt, Ian Leslie
This paper describes a system for the visualization of multiple protocols. The visualizer makes possible the identification of both intra and inter-protocol behaviour. This tool has become a critical...
The Effect of Early Packet Loss on Web Page Download Times (2003)
James Hall, Ian Pratt, Ian Leslie, Andrew Moore
Identification of the various elements contributing to the download time of Web objects has been the subject of much research. It is, however, the download time of a set of objects comprising an...
Summary of biosurveillance-relevant technologies (2003)
Andrew Moore, Greg Cooper, Rich Tsui, Mike Wagner
This short report, compiled upon request from Dave Siegrist and Ted Senator, surveys the spectrum of technologies that can help with Biosurveillance. We indicate which we have chosen, so far, to use...
cGraph: A Fast Graph-Based Method for Link Analysis and Queries (2003)
Jeremy Kubica, Andrew Moore, David Cohn, Jeff Schneider
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of entities. However,...
Bayesian Network Anomaly Pattern Detection for Disease Outbreaks (2003)
Weng-Keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner
Early disease outbreak detection systems typically monitor health care data for irregularities by comparing the distribution of recent data against a baseline distribution. Determining the baseline...
We show how a conceptually simple search operator called Optimal Reinsertion can be applied to learning Bayesian Network structure from data. On each step we pick a node called the target. We delete...
K-groups: Tractable Group Detection on (2003)
Jeremy Kubica, Andrew Moore, Jeff Schneider
Discovering underlying structure from co-occurrence data is an important task in many fields, including: insurance, intelligence, criminal investigation, epidemiology, human resources, and marketing....
Probabilistic noise identification and data cleaning (2003)
Real world data is never as perfect as we would like it to be and can often suffer from corruptions that may impact interpretations of the data, models created from the data, and decisions made based...
cgraph: A fast graph-based method for link analysis and queries (2003)
Jeremy Kubica, Andrew Moore, David Cohn, Jeff Schneider
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of entities. However,...
James D Thomas, Andrew Moore, Bryan Routledge, Blake Lebaron
This thesis is dedicated to Ednah Thomas, who showed me language; and Victor Yonash, who showed me computers. Abstract AI has long been applied to the problem of predicting financial markets. While...
cgraph: A fast graph-based method for link analysis and queries (2003)
Jeremy Kubica, Andrew Moore, David Cohn, Jeff Schneider
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of entities. However,...
K-groups: Tractable Group Detection onLarge Link Data Sets (2003)
Jeremy Kubica, Andrew Moore, Jeff Schneider
To this end, we present k-groups- an algorithm that uses an approach similar tothat of k-means (hard clustering and localized updates) to significantly accelerate the discovery of the underlying...
Jeremy Kubica, Andrew Moore, David Cohn, Jeff Schneider
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of entities. However,...
Multi-Protocol Visualization (2003)
Tool Demonstration James, James Hall, Andrew Moore, Ian Pratt, Ian Leslie
This paper describes a system for the visualization of multiple protocols. The visualizer makes possible the identification of both intra and inter-protocol behaviour. This tool has become a critical...
Tractable group detection on large link data sets (2003)
Jeremy Kubica, Andrew Moore, Jeff Schneider
Discovering underlying structure from co-occurrence data is an important task in many fields, including: insurance, intelligence, criminal investigation, epidemiology, human resources, and marketing....
Empirical Bayes Screening for Link Analysis (2003)
The domain of link analysis has recently re-ignited interest among researchers due to its applicability to new areas such as intelligence analysis (for example, identifying cliques of suspicious...
We show how a conceptually simple search operator called Optimal Reinsertion can be applied to learning Bayesian Network structure from data.
Rule-based Anomaly Pattern Detection for Detecting Disease Outbreaks (2002)
Weng-keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner
This paper presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns. Traditional techniques for anomaly...
Real-valued all-dimensions search: Low-overhead rapid searching over subsets of attributes (2002)
This paper is about searching the combinatorial space of contingency tables during the inner loop of a nonlinear statistical optimization. Examples of this operation in various data analytic...
Using Tarjan’s red rule for fast dependency tree construction (2002)
We focus on the problem of efficient learning of dependency trees. It is well-known that given the pairwise mutual information coefficients, a minimum-weight spanning tree algorithm solves this...
Variable resolution discretization in optimal control (2002)
Abstract. The problem of state abstraction is of central importance in optimal control, reinforcement learning and Markov decision processes. This paper studies the case of variable resolution state...
Using Tarjan’s red rule for fast dependency tree construction (2002)
We focus on the problem of efficient learning of dependency trees. It is well-known that given the pairwise mutual information coefficients, a minimum-weight spanning tree algorithm solves this...
Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks (2002)
Weng-keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner
This paper presents an algorithm for performing early detection of disease outbreaks by searching a database of emergency department cases for anomalous patterns.
Interpolating conditional density trees (2002)
Joint distributions over many variables are frequently modeled by decomposing them into products of simpler, lower-dimensional conditional distributions, such as in sparsely connected Bayesian...
Active Learning in Discrete Input Spaces (2002)
Traditional design of experiments (DOE) from the statistics literature focuses on optimizing an output parameter over a space of continuous input parameters. Here we consider DOE, or active learning,...
Using Tarjan’s red rule for fast dependency tree construction (2002)
We focus on the problem of efficient learning of dependency trees. It is well-known that given the pairwise mutual information coefficients, a minimum-weight spanning tree algorithm solves this...
Using Tarjan’s red rule for fast dependency tree construction (2002)
We focus on the problem of efficient learning of dependency trees. It is well-known that given the pairwise mutual information coefficients, a minimum-weight spanning tree algorithm solves this...
Probabilistic Noise Identification and Data Cleaning (2002)
Real world data is never as perfect as we would like it to be and can often suffer from corruptions that may impact interpretations of the data, models created from the data, and decisions made based...
Summary of Biosurveillance-relevant statistical and data mining technologies (2002)
Andrew Moore, Greg Cooper, Rich Tsui, Mike Wagner
this document (or elsewhere) construct a detailed spatio-temporal probabilistic causal model of the population and use that model to infer the disease status of (1) the population and (2) each member...
Controlling the False Discovery Rate in Astrophysical Data Analysis (2001)
Miller, Christopher J., Genovese, Christopher, Nichol, Robert C., Wasserman, Larry, Connolly, Andrew, Reichart, Daniel, ...
The False Discovery Rate (FDR) is a new statistical procedure to control the number of mistakes made when performing multiple hypothesis tests, i.e. when comparing many data against a given model...
Carol Lonsdale NASA Infrared Processing and Analysis Center (2001)
Science Foundation, Paul Messina, Alex Szalay, Alyssa Goodman, Stephen Kent Fermilab, Tom Mcglynn Gsfc/heasarc/usra, ...
astronomical surveys to produce terabytes of images and catalogs. These datasets will cover the sky in different wavebands, from gamma-and X-rays, optical, infrared, through to radio. In a few years...
Mixtures of rectangles: Interpretable soft clustering (2001)
To be effective, data-mining has to conclude with a succinct description of the data. To this end, we explore a clustering technique that finds dense regions in data. By constraining our model in a...
Reinforcement Learning for Cooperating and Communicating Reactive Agents (2001)
Martin Riedmiller, Andrew Moore, Je Schneider
Abstract. Social behaviour in intelligent agent systems is often considered to be achieved by deliberative, in-depth reasoning techniques. This paper shows, how a purely reactive multi-agent system...
Fast Algorithms and Efficient Statistics: N-point Correlation Functions (2000)
Moore, Andrew, Connolly, Andy, Genovese, Chris, Gray, Alex, Grone, Larry, Kanidoris II, Nick, ...
We present here a new algorithm for the fast computation of N-point correlation functions in large astronomical data sets. The algorithm is based on kdtrees which are decorated with cached sufficient...
X-means: Extending K-means with efficient estimation of the number of clusters (2000)
Despite its popularity for general clustering, K-means suffers three major shortcomings; it scales poorly computationally, the number of clusters / ( has to be supplied by the user, and the search is...
Recently developed techniques have made it possible to quickly learn accurate probability density functions from data in low-dimensional continuous spaces. In particular, mixtures of Gaussians can be...
X-means: Extending K-means with Efficient Estimation of the Number of Clusters (2000)
Despite its popularity for general clustering, K-means suffers three major shortcomings; it scales poorly computationally, the number of clusters K has to be supplied by the user, and the search is...
Recently developed techniques have made it possible to quickly learn accurate probability density functions from data in low-dimensional continuous spaces. In particular, mixtures of Gaussians can be...
Mix-nets: Factored Mixtures of Gaussians in (2000)
Bayesian Networks With, Scott Davies, Andrew Moore
Recently developed techniques have made it possible to quickly learn accurate probability density functions from data in low-dimensional continuous spaces. In particular, mixtures of Gaussians can be...
Visual NRM User’s Manual (2000)
Approved for public release; distribution unlimited. NRL/FR/5540--00-9950
Working Group for Planetary System Nomenclature, in 16th General Assembly (1999)
This paper addresses the difficult problem of deciding where to refine the resolution of adaptive discretizations for solving continuous time-and-space deterministic optimal control problems. We...
Very fast EM-based mixture model clustering using multiresolution KD-trees (1999)
Clustering is importantinmany elds including manufacturing, biology, nance, and astronomy. Mixture models are a popular approach due to their statistical foundations, and EM is a very popular method...
Gradient descent for general reinforcement learning (1999)
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number of open problems,...
Distributed value functions (1999)
Jeff Schneider, Weng-keen Wong, Andrew Moore, Martin Riedmiller
Many interesting problems, such as power grids, network switches, and traffic flow, that are candidates for solving with reinforcement learning (RL), also have properties that make distributed...
Very fast EM-based mixture model clustering using multiresolution KD-trees (1999)
Clustering is important in many fields including manufacturing, biology, finance, and astronomy. Mixture models are a popular approach due to their statistical foundations, and EM is a very popular...
Bayesian Networks for Lossless Dataset Compression (1999)
The recent explosion in research on probabilistic data mining algorithms such as Bayesian networks has been focussed primarily on their use in diagnostics, prediction and efficient inference. In this...
Efficient Multi-Object Dynamic Query Histograms (1999)
Mark Derthick, James Harrison, Andrew Moore, Steven F. Roth
Dynamic Queries offer continuous feedback during range queries, and have been shown to be effective and satisfying. Recent work has extended them to datasets of 100,000 objects and, separately, to...
Cached Sufficient Statistics for Automated Mining and Discovery from Massive Data Sources (1999)
Andrew Moore, Jeff Schneider, Paul Komarek, Remi Munos, Kary Myers, Dan Pelleg
ual analysis of such data sources is now passing from being simply tedious into a new, fundamentally impossible realm where the data sources are just too large to assimilate by humans. This situation...
Variable Resolution Discretization for High-Accuracy Solutions of Optimal Control Problems (1999)
State abstraction is of central importance in reinforcement learning and Markov Decision Processes. This paper studies the case of variable resolution state abstraction for continuous-state,...
Variable Resolution Discretization in Optimal Control (1999)
Rémi Munos, Andrew Moore, Satinder Singh
. The problem of state abstraction is of central importance in optimal control, reinforcement learning and Markov decision processes. This paper studies the case of variable resolution state...
Multi-Value-Functions: Efficient Automatic Action Hierarchies for Multiple Goal MDPs (1999)
Andrew Moore, Leemon Baird, Leslie Pack Kaelbling
In goal-based Markov Decision Problems, it is usual to generate... Actions come from?", and whether it is necessary to have some high-level prior understanding of the class of tasks at hand in...
Very fast EM-based mixture model clustering using multiresolution KD-trees (1999)
Clustering is important in many elds including manufacturing, biology, nance, and astronomy. Mixture models are a popular approach due to their statistical foundations, and EM is a very popular...
Accelerating exact k-means algorithms with geometric reasoning (1999)
We present new algorithms for the k-means clustering problem. They use the kd-tree data structure to reduce the large number of nearest-neighbor queries issued by the traditional algorithm. Su cient...
Working Group for Planetary System Nomenclature, in 16th General Assembly (1999)
This paper addresses the difficult problem of deciding where to refine the resolution of adaptive discretizations for solving continuous time-and-space deterministic optimal control problems. We...
Gradient descent for general reinforcement learning (1999)
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number of open problems,...
Efficient multi-object dynamic query histograms (1999)
Mark Derthick, James Harrison, Andrew Moore, Steven F. Roth
Dynamic Queries offer continuous feedback during range queries, and have been shown to be effective and satisfying. Recent work has extended them to datasets of 100,000 objects and, separately, to...
Gradient descent for general reinforcement learning (1999)
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number of open problems,...
Accelerating exact k-means algorithms with geometric reasoning (1999)
We present new algorithms for the k-means clustering problem. They use the kd-tree data structure to reduce the large number of nearest-neighbor queries issued by the traditional algorithm. Su cient...
Accelerating exact k-means algorithms with geometric reasoning (1999)
An extract of this work appeared in KDD-99.
External COMSEC Adaptor Software Engineering Methodology. (1998)
Moore, Andrew, Chapman, Eather, Kim, David, Klinker, Eric, Hayman, Kenneth
The External COMSEC Adaptor (ECA) is a device responsible for providing cryptographic protection of information based on rule that (possibly coarsely) define the sensitivity of that information. The...
Accelerating Exact k-means Algorithms with Geometric Reasoning (1998)
We present new algorithms for the k-means clustering problem. They use the kd-tree data structure to reduce the large number of nearest-neighbor queries issued by the traditional algorithm....
Recently developed techniques have made it possible to quickly learn accurate probability density functions from data in low-dimensional continuous spaces. In particular. mixtures of Gaussians can be...
A Methodology, a Language, and a Tool to Provide Information Security Assurance Arguments (1998)
Park, Joon, Moore, Andrew, Montrose, Bruce, Strohmayer, Beth, Froscher, Judith
As information systems become more complex and industry and military rely more on their correct operation, the need for survivable, secure systems becomes more pressing. System designers and...
Insider Threat Study: Illicit Cyber Activity in the Banking and Finance Sector (1998)
Randazzo, Marisa R., Keeney, Michelle, Kowalski, Eileen, Cappelli, Dawn, Moore, Andrew
Current and former employees, contractors, and other organizational "insiders" pose a substantial threat by virtue of their knowledge of and access to their employers' systems and/or databases and...
Realism and Christian faith : God grammar, and meaning / (1998)
Moore, Andrew (Andrew Jonathan)
Thesis (D. Phil.)--University of Oxford, 1998.
Experimental results from a practical implementation of a Measurement Based CAC algorithm (1998)
Interest in Connection Admission Control (CAC) algorithms stems from the need for a network user and a network provider to forge an agreement on the Quality of Service (QoS) for a connection the user...
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets (1998)
This paper introduces new algorithms and data structures for quick counting for machine learning datasets. We focus on the counting task of constructing contingency tables, but our approach is also...
Barycentric interpolators for continuous space & time reinforcement learning (1998)
In order to find the optimal control of continuous state-space and time reinforcement learning (RL) problems, we approximate the value function (VF) with a particular class of functions called the...
ADtrees for fast counting and for fast learning of association rules (1998)
Brigham Anderson, Andrew Moore
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all association rules...
Applying Online Search Techniques to Continuous-State Reinforcement Learning (1998)
Scott Davies, Andrew Y. Ng, Andrew Moore
In this paper, we describe methods for efficiently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boost the power of...
Applying Online Search Techniques to Reinforcement Learning (1998)
Scott Davies, Andrew Y. Ng, Andrew Moore
In reinforcement learning it is frequently necessary to resort to an approximation to the true optimal value function. Here we investigate the benefits of online search in such cases. We examine...
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets (1998)
This paper introduces new algorithms and data structures for quick counting for machine learning datasets. We focus on the counting task of constructing contingency tables, but our approach is also...
Applying online search techniques to reinforcement learning (1998)
Scott Davies, Andrew Y. Ng, Andrew Moore
In reinforcement learning it is frequently necessary to resort to an approximation to the true optimal value function. Here we investigate the bene ts of online search in such cases. We examine...
Barycentric interpolators for continuous space and time reinforcement learning (1998)
In order to nd the optimal control of continuous state-space and time reinforcement learning (RL) problems, we approximate the value function (VF) with a particular class of functions called the...
Cached Sufficient Statistics for Efficient Machine Learning with Large Datasets (1998)
This paper introduces new algorithms and data structures for quick counting for machine learning datasets. We focus on the counting task of constructing contingency tables, but our approach is also...
Commentary on "Psychological Courage" (1997)
Philosophy, Psychiatry, & Psychology - Volume 4, Number 1, March 1997
External COMSEC adaptor software engineering methodology (1995)
Andrew Moore, Eather Chapman, David Kim, Eric Klinker, David Mihelcic, Charles Payne, ...
Approved for public release; distribution unlimited. NRL/MR/5542--95-7768 The External COMSEC Adaptor (ECA) is a device responsible for providing cryptographic protection of information based on...
University Microfilms order no. UMI00293615.
A Delay-Line Based Motion Detection Chip (1991)
Tim Horiuchi John, John Lazzaro, Andrew Moore, Christof Koch
Inspired by a visual motion detection model for the rabbit retina and by a computational architecture used for early audition in the barn owl, we have designed a chip that employs a correlation model...
A Delay-Line Based Motion Detection Chip (1991)
Tim Horiuchi, John Lazzaro, Andrew Moore, Christof Koch
Inspired by a visual motion detection model for the rabbit retina and by a computational architecture used for early audition in the barn owl, we have designed a chip that employs a correlation model...
A Delay-Line Based Motion Detection Chip (1991)
Tim Horiuchi, John Lazzaro, Andrew Moore, Christof Koch
Inspired by a visual motion detection model for the rabbit retina and by a computational architecture used for early audition in the barn owl, we have designed a chip that employs a correlation model...
Dongryeol Lee, Alexander Gray, Andrew Moore
In previous work we presented an efficient approach to computing kernel summations which arise in many machine learning methods such as kernel density estimation. This approach, dual-tree recursion...
Dongryeol Lee, Alexander Gray, Andrew Moore
In previous work we presented an efficient approach to computing kernel summations which arise in many machine learning methods such as kernel density estimation. This approach, dual-tree recursion...
Written for the Dept. of Chemistry.
The effect of ligand structure on the reactivity of a diverse group of aqua-hydroxytetraazacobalt(III) complexes towards the hydrolysis of phosphate diesters and carboxylic esters has been...
The effect of ligand structure on the reactivity of a diverse group of aqua-hydroxytetraazacobalt(III) complexes towards the hydrolysis of phosphate diesters and carboxylic esters has been...
Thesis (B.A. (Hons.)-History)-University of Natal, Durban, 1985.
Typescript.
Falling leaves [music] / (1850)
For voice and piano.; Cover title.; "Composed and dedicated to Mrs. Henry Marsh.".; Engraved.; Also available in an electronic version via the Internet at: http://nla.gov.au/nla.mus-vn3601941.
Goebel, Andreas, Moore, Andrew, Weatherall, Rosamund, Roewer, Norbert, Schedel, Robert, Sprotte, Guenter
Learning from PISA: Reasons and remedies for student under-performance in reading, maths and science
Waiter, there's a nanobot in my martini!
As nanotechnology gives birth to nanobiotechnology, definitions and perceptions are at risk of becoming mixed into an exotic cocktail
The experienced, highly qualified postdoc is a valuable resource. Is academia ready to create a niche for this species?
The use of friendly microbes to thwart pathogens has a long history. Will the latest wave of discoveries bring us any closer to new biological medicines?
The ten new EU member states have an uphill battle to improve their science base, but would prefer not to play by different rules from the rest
Descartes' Europe: one good revolution deserves another
The established Descartes Prize for Research is joined by the Descartes Prize for Science Communication. The message—no progress without communication
Short-circuiting our fossil fuel habits
Could a more direct harnessing of photosynthesis become an alternative to natural oil, coal and gas?
What you don't learn at the bench…
Conclusions from the EMBO/ELSF-organised meeting on career prospects in the life sciences
The big and small of drug discovery
Biotech versus pharma: advantages and drawbacks in drug development
Genomics and proteomics may provide new ways of making the lives of bacteria more miserable
The USA and the EU are getting into another squabble over genetically modified crops
Breathing new life into the biology classroom
An increasing number of exciting experiments for teaching biology is becoming available, but teacher training and institutional reform are also needed to integrate them into curricula
What's in store for animal research in the EU?
Researchers should have little to fear from the EU's new animal-welfare directive, but the menace is in the minutiae
The heat is on for many species: adapt to global warming or die. How are organisms and ecologies changing, and how much should we care?
Goebel, Andreas, Moore, Andrew, Weatherall, Rosamund, Roewer, Norbert, Schedel, Robert, Sprotte, Guenter
Learning from PISA: Reasons and remedies for student under-performance in reading, maths and science
Waiter, there's a nanobot in my martini!
As nanotechnology gives birth to nanobiotechnology, definitions and perceptions are at risk of becoming mixed into an exotic cocktail
The experienced, highly qualified postdoc is a valuable resource. Is academia ready to create a niche for this species?
The use of friendly microbes to thwart pathogens has a long history. Will the latest wave of discoveries bring us any closer to new biological medicines?
The ten new EU member states have an uphill battle to improve their science base, but would prefer not to play by different rules from the rest
Descartes' Europe: one good revolution deserves another
The established Descartes Prize for Research is joined by the Descartes Prize for Science Communication. The message—no progress without communication
Short-circuiting our fossil fuel habits
Could a more direct harnessing of photosynthesis become an alternative to natural oil, coal and gas?
What you don't learn at the bench…
Conclusions from the EMBO/ELSF-organised meeting on career prospects in the life sciences
The big and small of drug discovery
Biotech versus pharma: advantages and drawbacks in drug development
Genomics and proteomics may provide new ways of making the lives of bacteria more miserable
The USA and the EU are getting into another squabble over genetically modified crops
Breathing new life into the biology classroom
An increasing number of exciting experiments for teaching biology is becoming available, but teacher training and institutional reform are also needed to integrate them into curricula
What's in store for animal research in the EU?
Researchers should have little to fear from the EU's new animal-welfare directive, but the menace is in the minutiae
The heat is on for many species: adapt to global warming or die. How are organisms and ecologies changing, and how much should we care?
Andrew Moore, Ceri Phillips, Elke Hunsche, James Pellissier, Simone Crespi
Introduction: The objective of this study was to evaluate the potential economic implications of using etoricoxib versus non-selective NSAID alternatives in the treatment of patients with...
Andrew Moore, Ceri Phillips, Elke Hunsche, James Pellissier, Simone Crespi
Etoricoxib, Gastric-haemorrhage, Nonsteroidal-anti-inflammatories, Osteoarthritis, Proton-pump-inhibitors, Rheumatoid-arthritis
Tsui, Fu-Chiang, Espino, Jeremy U., Wagner, Michael M., Gesteland, Per, Ivanov, Oleg, Olszewski, Robert T., ...
Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based...
Accelerating Exact k-means Algorithms with Geometric Reasoning
We present new algorithms for the k-means clustering problem. They use the kd-tree data structure to reduce the large number of nearest-neighbor queries issued by the traditional algorithm....