Martinez, Tony R. - Department of Computer Science, Brigham Young University

• LocationIndependent Neural Network Models A Dissertation
• Using Precepts to Augment Training Set Learning 1 Christophe GiraudCarrier and Tony Martinez
• DO NOT DELETE 2/1/2011 7:16 PM Can States "Just Say No" to Federal Health Care
• Herman Teule is chair of Eastern Christianity and head of the Institute of Eastern Christian Studies at the
• Extending Occam's Razor Kevin S. Van Horn & Tony R. Martinez
• BA in AMERICAN STUDIES (570120) Map Sheet College of Humanities
• Proceedings of the International Conference on Artificial Intelligence, Expert Systems and Neural Networks (AIE'96), pp. 11-14, 1996.
• Chapter 2 1892 -1900 Brigham Young University -Founder's Day -1900
• Pair Attribute Learning: Network Construction Using Pair Features
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• Implementing Competitive Learning in a Quantum System Dan Ventura
• Proceedings of the 10th International Symposium on Computer and Information Sciences, pp. 411418, 1995. NPCompleteness of Minimum Rule Sets
• In Proceedings of the IEEE Symposium on Parallel and Distributed Computing, pp. 308315, 1989. On the Pseudo Multilayer Learning of Backpropagation
• Machine Learning, 383, pp. 257--286 (2000) fl 2000 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
• IMPROVED HOPFIELD NETWORKS BY TRAINING WITH NOISY DATA Fred Clift and Tony R. Martinez
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• Proceedings of the International Joint Conference on Neural Networks, pp. 103641, May 1998 Optimal Control Using a Neural/Evolutionary Hybrid System
• In WCNN'93 World Congress on Neural Networks, vol. I, pp. 613616, 1993. A Generalizing Adaptive Discriminant Network
• Improving Text Classification by Using Conceptual and Contextual Features
• In Proceedings of the IASTED International Symposium on Expert Systems and Neural Networks, pp. 1215, 1989. DNA: A New ASOCS Model
• An Artificial Neuron with Quantum Mechanical Properties Dan Ventura and Tony Martinez
• In IWANNT'93 International Workshop on Applications of Neural Networks to Telecommuniations, pp. 183187, 1993. A Learning Model for Adaptive Network Routing
• Aerial view of Brigham Young University Upper Campus -1954 Chapter 61951 -1957
• The Mission of Brigham Young University The mission of Brigham Young University--founded, supported, and guided by The Church of Jesus Christ of Latter-day
• Revised 2/15/2006 THESIS/DISSERTATION GUIDELINES
• To appear in International Journal of Neural Systems + This research is funded in part by grants from Novell Inc. and Word Perfect Corp.
• Chapter 132005 -Brigham Young University -2005
• INTERNATIONAL INTERNSHIP AFFILIATION MEMORANDUM OF UNDERSTANDING
• AAA Style Guide AAA uses The Chicago Manual of Style (14th edition, 1993) and Merriam-Webster's Collegiate
• Donald W. Forsyth Department of Anthropology
• Completing the Tenant Checklist 1. Go to http://www.byu.edu/offcampushousing/
• Rival Approaches: Old and New For two decades processual and postprocessual archaeologists have
• G R A N T T A G G A R T S Y M P O S I U M B R I G H A M Y O U N G U N I V E R S I T Y Join us for the best conference yet!
• Sentiment Regression: Using Real-Valued Scores to Summarize Overall Document Sentiment
• Paris Hilton and Meryl Streep they're both famous actors, but they seem to have extremely different approaches to acting. While Paris Hilton's goals seem to be concerned with obtaining attention and fame,
• Undergraduate Department Tuition Scholarships APPLICATION
• Proceedings of the International Conference on Artificial Intelligence, Expert Systems and Neural Networks (AIE'96), pp. 1114, 1996.
• In Fisher, D., ed., Machine Learning: Proceedings of the Fourteenth International Conference, Morgan Kaufmann Publishers, San Francisco, CA, pp. 404411, 1997.
• Proceedings of the 6th Australian Joint Conference on Artificial Intelligence (AI'93), pp. 356361, Nov. 1993. The Potential of Prototype Styles of Generalization +
• COD: Measuring the similarity of classifiers Adam H. Peterson
• Proceedings of the International Conference on Computational Intelligence and Neuroscience, vol. 2, pp. 218221, October 1998.
• In Proceedings of the 2nd Government Neural Network Workshop, 1991. ASOCS: Towards Bridging Neural Network and Artificial Intelligence Learning
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• A Sub-symbolic Model of the Cognitive Processes of Re-representation and Insight
• (801) 422-4789 Email: Humanities-advisement@byu.edu
• The Hanging of Absalom, a wall-hanging attributed to Faith Robinson Trumbull, uses biblical imagery to symbolically depict events of colonial America.
• 2011-2012 GRADUATE SCHOLARSHIP APPLICATION Upd: 2/23/11 Civil and Environmental Engineering --Scholarship Society
• Effectively Using Recurrently Connected Spiking Neural Networks
• Martin Luther King Jr. and other black activists were imprisoned but continued the civil rights movement from behind bars.
• Requirements Career Goals and Academic Focus
• DO NOT DELETE 2/16/2011 1:00 PM The Dictionary Is Not a Fortress: Definitional
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• In International Journal on Artificial Intelligence Tools, vol. 3, No. 3, pp. 417427, 1994. LOCATIONINDEPENDENT TRANSFORMATIONS
• In proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 4144, + This research is funded by grants from Novell Inc. and Word Perfect Corp.
• Optimization by Varied Beam Search in Hopfield Networks Xinchuan Zeng and Tony R. Martinez
• Proceedings of the 2nd International Symposium on Neuroinformatics and Neurocomputers, pp. 7784, 1995. A Provably Convergent Dynamic Training Method for
• Lazy Training: Improving Backpropagation Learning through Network Interaction
• A PreceptDriven Learning Algorithm Presented to the
• In Progress in Neural Networks, vol. 1, Ch. 5, pp. 105126, O. Omidvar (ed), Ablex Publishing, 1990. Adaptive SelfOrganizing Concurrent Systems
• Completing the Masters Program in 8 Easy Steps
• A Quantum Associative Memory Based on Grover's Algorithm Dan Ventura and Tony Martinez
• AIM Access Request Access to confidential student information is protected under the Family Educational Rights and Privacy Act (FERPA), and
• Adult Contemporary Dance Summer Intensive July 1122, 2011 2011ACD-874 City State Zip Code
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• To appear in Neural Networks, 2003. The General Inefficiency of Batch Training
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• "Organize Yourselves According to the Laws of Man"
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• Probabilistic Connections in Relaxation Networks Dan Ventura
• Conference on Computerized Family History and Genealogy http://ce.byu.edu/cw/cwcompu/[9/28/2010 2:32:33 PM]
• Material adapted from Anastasia Pryanikova, "How to Form an Effective Study Group," Lawsagna: neuroscience-fueled tips for productivity, creativity and influence, http://lawsagna.typepad.com/lawsagna/2007/04 /how_to form_an_.html; The College Board, "The
• Network Simplification Through Oracle Learning Joshua Menke, Adam Peterson, Mike Rimer, Tony Martinez
• Reference: WCNN, pp 177181, 1996. The Effect of Decision Surface Fitness on
• Proceedings of the 10th International Symposium on Computer and Information Sciences, pp. 419426, 1995. Learning and Generalization with Bounded Order Rule Sets
• Chapter 121993-2005 Brigham Young University -1999
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• Call for Papers 2010 BYU Computerized Genealogy
• Towards Automatic Shaping in Robot Navigation Todd S. Peterson, Nancy E. Owens & James L. Carroll
• Computational Intelligence, Volume 16, Number 1, pp. 128, 2000 1999 Blackwell Publishers, 238 Main Street, Cambridge, MA 02142, USA, and 108 Cowley Road, Oxford, OX41JF, UK.
• Student Academic Record Petition Employer's Verification Form
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• Proceedings of the International Symposium on Neuroinformatics and Neurocomputers, pp. 238-45, 1995 Using Multiple Statistical Prototypes to Classify Continuously Valued Data
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• BYU CONFERENCES AND WORKSHOPS FINANCIAL AID APPLICATION 2011
• By ALICIA MOULTON From Karl G. Maeser to Benjamin Cluff persevering amidst
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• Proceedings of the Seventh Florida Artificial Intelligence Research Symposium, pp. 11721, 1994 BRACE: A Paradigm For the Discretization of
• Using A Neural Network to Approximate An Ensemble of Classifiers
• A Neural Model of Centered Trigram Speech Recognition Dan Ventura, D. Randall Wilson and Brian Moncur
• In Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, (ICANNGA'97), pp. 514517, 1997.
• VisCom Web Team | Brigham Young University, Provo, UT 84602 -(801)422-4636 -Copyright 2007, All Rights Reserved Conference on Computerized Family History and Genealogy
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• Generating Three Binary Addition Algorithms using Reinforcement Programming
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• In Proceedings of the 2001 International Joint Conference on Neural Networks (IJCNN'01), 115-119. The Need for Small Learning Rates
• Quantum associative memory with distributed queries A. A. Ezhov*
• HEALTH CARE REFORM AND ITS EFFECT ON STUDENT HEALTH PLANS INTRODUCTION
• Optimal Artificial Neural Network Architecture Selection for Bagging Tim Andersen
• A Practical Generalization of Fourier-based Learning Adam Drake acd2@cs.byu.edu
• On Discretization as a Preprocessing Step For Supervised Learning Models
• Journal of Artificial Intelligence Research 3 (1995) 147185 Submitted 8/94; published 8/95 An Integrated Framework for Learning and Reasoning
• Improving the Hopfield Network through Beam Search Xinchuan Zeng and Tony R. Martinez
• In Proceedings of the 1997 Sian Ka'an International Workshop on Neural Networks and Neurocontrol. RealValued Schemata Search Using Statistical Confidence
• In WCNN'93 World Congress on Neural Networks, vol. III, pp. 376380, 1993. GS: A Network that Learns Important Features
• A New Activation Function in the Hopfield Network for Solving Optimization Problems \Lambda
• Learning a Rendezvous Task with Dynamic Joint Action Perception Nancy Fulda and Dan Ventura
• Artificial Neural Network Reduction Through Oracle Learning
• AP/IB Credit 20052006 ADVANCED PLACEMENT CREDIT AT BRIGHAM YOUNG UNIVERSITY 2006
• DEPARTMENTOF HISTORY SCHOLARSHIP INFORMATION DEADLINE: February 1, 2011
• Using Multiple Measures to Predict Confidence in Instance Classification
• An Artificial Neuron with Quantum Mechanical Properties Dan Ventura and Tony Martinez
• Softprop: Softmax Neural Network Backpropagation Learning
• Improving Speech Recognition Learning through Lazy Training Michael E. Rimer
• In ANNES'93 Conference on Artificial Neural Networks and Expert Systems, pp. 216219, 1993. Towards a General Distributed Platform for Learning and Generalization +
• In IEEE Transactions on Systems, Man, and Cybernetics, vol. 24, No. 3, pp. 503510, 1994. Proof of Correctness for ASOCS AA3 Networks 1
• In Artificial Neural Networks, Kohonen, et. al. (eds), Elsevier Science Publishers, pp. 729734, 1991. AN EFFICIENT STATIC TOPOLOGY FOR MODELING ASOCS
• USPS No. 065-120 To order a copy of this catalog, please send $5, plus $3 for post-
• Have the experience provider complete the In-ternship Master Agreement and Experience In-
• Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 46871, 1995
• Eclectic Machine Learning A Dissertation
• Proceedings of the International Conference on Neural Networks, pp. 524528, 1996 Robust Optimization Using Training Set Evolution
• In Journal of Parallel and Distributed Computing, vol. 11, No. 4, pp. 303313, 1991. A SelfAdjusting Dynamic Logic Module
• Extending ASOCS to TrainingSetStyle Data Presented to the
• The Little Neuron that Could Tim Andersen Tony Martinez
• A MultiChip Module Implementation of a Neural Network Matthew G. Stout George L. Rudolph
• In Future Generation Computing Systems, vol. 6, No. 1, pp.2658, 1990. Smart Memory Architecture and Methods
• AN EFFICIENT METRIC FOR HETEROGENEOUS INDUCTIVE LEARNING APPLICATIONS IN THE ATTRIBUTEVALUE LANGUAGE 1
• Using Decision Trees and Soft Labeling to Filter Mislabeled Data Xinchuan Zeng and Tony Martinez
• Chapter 5 1945 -1951 Aerial view of Brigham Young University Upper Campus -1950
• Graduate Handbook 2010-2011 GRADUATE HANDBOOK
• Predicting and Preventing Coordination Problems in Cooperative Q-learning Nancy Fulda and Dan Ventura
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• Proceedings of the International Workshop on Neural Networks and Neurocontrol, 1997 Neural Network and Machine Learning Laboratory
• AP/IB Credit 20032004 ADVANCED PLACEMENT CREDIT AT BRIGHAM YOUNG UNIVERSITY 2004
• A Neural Model of Centered Tri-gram Speech Recognition Dan Ventura, D. Randall Wilson and Brian Moncur
• A Quantum Associative Memory Based on Grover's Algorithm Dan Ventura and Tony Martinez
• In Proceedings of the International Conference on Intelligent Information Systems (IIS'97), pp. 108114, 1997. Bias and the Probability of Generalization
• In IEEE Systems, Man, and Cybernetics, vol. 21, No. 5, pp.12311238, 1991. A SelfOrganizing Binary Decision Tree For Incrementally Defined Rule Based
• Prioritized Rule Systems Presented to the
• In Journal of Artificial Neural Networks, vol. 1, no. 3, pp. 403429, 1994. Priority ASOCS
• Brigham Young University Ballroom Dance Camp
• Proceedings of the International Conference on Artificial Intelligence, Expert Systems and Neural Networks (AIE'96), pp. 11-14, 1996.
• The Robustness of Relaxation Rates in Constraint Satisfaction Networks D. Randall Wilson
• Welcome to camp! We are excited that you have chosen to improve your skills at the BYU Youth Ballroom Camp. Parents and participants: Please carefully read the following information regarding the camp. Should you have
• The BBG Rule Induction Algorithm Kevin S. Van Horn and Tony R. Martinez
• Chapter 101978-1981 Brigham Young University Campus -1978
• In International Journal of Neural Systems, vol. 12, no.3&4, pp. 303-318. IMPROVED BACKPROPAGATION LEARNING IN NEURAL NETWORKS WITH
• IB Credit 20032004 INTERNATIONAL BACCALAUREATE PROGRAM 2004 TESTS
• "This Blessed House" explores camp--a style characterized by kitsch like this Jesus-themed snow globe--as a coping strategy for life in a material world.
• Brigham Young University Teacher Preparation ProgramBrigham Young University Teacher Preparation Program University Council on Teacher EducationUniversity Council on Teacher Education
• Real-time Automatic Price Prediction for eBay Online Trading Ilya Raykhel and Dan Ventura
• AP/IB Credit 20022003 ADVANCED PLACEMENT CREDIT AT BRIGHAM YOUNG UNIVERSITY 2003
• Extending the Power and Capacity of Constraint Satisfaction Networks \Lambda
• On Integrating Inductive Learning with Prior Knowledge and Reasoning A Dissertation
• Graded Rescaling in Hopfield Networks Xinchuan Zeng, Tony R. Martinez
• Memoryguided Exploration in Reinforcement Learning James L. Carroll, Todd S. Peterson & Nancy E. Owens
• Estimating The Potential for Combining Learning Models Adam H. Peterson adam@axon.cs.byu.edu
• Memory-guided Exploration in Reinforcement Learning James L. Carroll, Todd S. Peterson & Nancy E. Owens
• August 14, 2011 Registration begins Wednesday, February 9, 2011
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• Music Recommendation and Query-by-Content Using Self-Organizing Maps
• DMP3: A Dynamic Multilayer Perceptron Construction Algorithm Tim L. Andersen and Tony R. Martinez
• Constructing High Order Perceptrons with Genetic Algrithms Tim Andersen and Tony Martinez
• Incremental Policy Learning: An Equilibrium Selection Algorithm for Reinforcement Learning
• Target Sets: A Tool for Understanding and Predicting the Behavior of Interacting Q-learners
• Towards Automatic Shaping in Robot Navigation Todd S. Peterson, Nancy E. Owens & James L. Carroll
• 0-7803-7087-2/01/$10.00 2001 IEEE Using a Reinforcement Learning Controller to Overcome
• Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous
• Iterative Non-linear Dimensionality Reduction by Manifold Sculpting
• A Constructive Incremental Learning Algorithm for Binary Classification Tasks
• Spatiotemporal Pattern Recognition via Liquid State Machines Eric Goodman, Sandia National Laboratories, and Dan Ventura, Brigham Young University
• CONSTRUCTING LOW-ORDER DISCRIMINANT NEURAL NETWORKS USING STATISTICAL FEATURE SELECTION
• ORIGINAL ARTICLE A BradleyTerry artificial neural network model for individual
• Using Permutations Instead of Student's t Distribution for p-values in Paired-Difference
• Automatic Generation of Music for Inducing Emotive Response
• To appear in Intelligent Data Analysis, vol. 7, no. 6, 2003. Weighted Instance Typicality Search (WITS)
• Choosing a Starting Configuration for Particle Swarm Optimization
• Dynamic Sociometry in Particle Swarm Optimization Mark Richards and Dan Ventura
• CB3: An Adaptive Error Function for Backpropagation Training
• Improving Classification Accuracy by Identifying and Removing Instances that Should Be Misclassified
• Time Series Gene Expression Prediction using Neural Networks with Hidden Layers
• THE HOUGH TRANSFORM'S IMPLICIT BAYESIAN FOUNDATION Neil Toronto, Bryan S. Morse, Dan Ventura, Kevin Seppi
• Learning Quantum Operators From Quantum State Pairs
• Edge Inference for Image Interpolation Neil Toronto
• ADtrees for Sequential Data and N-gram Counting Rob Van Dam and Dan Ventura
• Learning as Optimization A Dissertation
• A Reductio Ad Absurdum Experiment in Sufficiency for Evaluating (Computational)
• Data-Driven Programming and Behavior for Autonomous Virtual Characters Jonathan Dinerstein, Parris K. Egbert, Dan Ventura and Michael Goodrich
• Abstract--Existing learning-based multi-modal biometric fusion techniques typically employ a single static Support
• Clustering Streaming Music via the Temporal Similarity of Timbre
• Geometric Task Decomposition in a Multi-Agent Environment Kaivan Kamali1
• Training a Quantum Neural Network Department of Computer Science
• Pattern Classification Using a Quantum System Dan Ventura
• A Quantum Analog to Basis Function Networks Dan Ventura
• Quantum neural networks Alexandr A. Ezhov1
• Proceedings of the International Joint Conference on Neural Networks, pp. 509-13, May 1998 Quantum Associative Memory with Exponential Capacity
• Proceedings of the International Joint Conference on Neural Networks, pp. 1036-41, May 1998 Optimal Control Using a Neural/Evolutionary Hybrid System
• Proceedings of the International Conference on Neural Networks, pp. 524-528, 1996 Robust Optimization Using Training Set Evolution
• Proceedings of the World Congress on Neural Networks, pp. 1091-5, 1996 A General Evolutionary/Neural Hybrid Approach to Learning Optimization Problems
• Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 468-71, 1995
• Proceedings of the Tenth International Symposium on Computer and Information Sciences, pp. 443-450, 1995 An Empirical Comparison of Discretization Methods
• In Proceedings of the International Joint Conference on Neural Networks (IJCNN2000), Vol. II, pp. 113-117, July 2000.
• Computational Intelligence, Volume 16, Number 1, pp. 1-28, 2000 1999 Blackwell Publishers, 238 Main Street, Cambridge, MA 02142, USA, and 108 Cowley Road, Oxford, OX41JF, UK.
• In Proceedings of the International Joint Conference on Neural Networks (IJCNN'99) , paper 163, 1999. Combining Cross-Validation and Confidence to Measure Fitness
• In Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, (ICANNGA'97), pp. 514-517, 1997.
• In Fisher, D., ed., Machine Learning: Proceedings of the Fourteenth International Conference, Morgan Kaufmann Publishers, San Francisco, CA, pp. 404-411, 1997.
• In Proceedings of the International Conference on Intelligent Information Systems (IIS'97), pp. 108-114, 1997. Bias and the Probability of Generalization
• Journal of Artificial Intelligence Research 6 (1997) 1-34 Submitted 5/96; published 1/97 1997 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.
• In Proceedings of the 1997 Sian Ka'an International Workshop on Neural Networks and Neurocontrol. Real-Valued Schemata Search Using Statistical Confidence
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• Rebecca Harding Davis sets her story of industrial poverty in an iron mill in a town such asWheeling,WestVirginia, represented here in Charles Graham's 1890 rendering.
• Mark Twain's Adventures of Huckleberry Finn deals with religious and cultural themes in the nineteenth-century setting of the banks of the Mississippi River.
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