Conference Program



December 16-18, 2004,

Galt House Hotel, Louisville, KY, USA

Thursday, December 16, 2004


Conference Room 1

Conference Room 2

8:00–5:00 pm



Opening Session


Invited Speakers:

Dr. Asim Smailagic,
Carnegie Mellon University:
Unsupervised Machine Learning and Cognitive Systems in Learning User State for Context-Aware Computing

Dr. Bhavani Thuraisingham,
University of Texas:
Data Mining for Security Applications


Coffee Break


Session 1:

Text and Web Mining

Session Chair:
Stephen Scott

104 , 177 , 170 , 157 , 124

Yi Sun, Timothy S. Butler, Alex Shafarenko, Rod Adams, Martin Loomes, and Neil Davey:
The Identifying Word Boundaries in Handwritten Text

Stephen Scott and Christopher N. Hammack:
LASSO: A Learning Architecture for Semantic Web Ontologies

Jai Li , H. Li and X. Jia:
A naïve Bayes Learning Based Website Reconfiguration System

Wu Chou, Li Li:
A Minimum Classification Error (MCE) Framework for Generalized Linear Classifier in Machine Learning and Its Application to Text Categorization/Retrieval

Tansel Ozyer, Reda Alhajj, and Ken Barker:
Multi-Dimensional Sequential Web Mining by Utilizing Fuzzy Inferencing

Session 2:

Machine Learning Techniques - 1

Session Chair:
Kevin Seppi

188 , 176 , 172 , 167 , 135

Yijun Sun, Jian Li, William Hager:
Two New Regularized AdaBoost Algorithms

James L. Carrol and Kevin Seppi:
A Bayesian Technique for Task Localization in Multiple Goal Markov Decision Processes

Jeremy A. Glasser and Leen-Kiat Soh:
Matching an Opponent’s Performance in a Real-Time, Dynamic Environment

Michael A. Goodrich, M. Quigley:
Satisficing Q-Learning: Efficient Learning in Problems with Dichotomous Attributes

Luis G. Moscovich and Jianhua Chen:
Learning Hidden Markov Model from the State Distribution Oracle


Lunch Break


Session 3:

Applications - 1

Session Chair:
Anup Kumar

107, 186 , 123 , 143 , 122

Miki Fukunari, K. P. Bennet, C. J. Malmborg:
Decision-Tree Learning In Dwell Point Policies In Autonomous Vehicle Storage And Retrieval Systems (AVSRS)

Sherif Rashad, Mehmed Kantardzic, and Anup Kumar:
Mobile Data Mining for Radio Resource Management in Wireless Mobile Networks

Gang Yu, Sagar V. Kamarthi, Stefan Pittner:
A New Cluster-Based Feature Extraction Method for Surface Detect Detection

Charles L. Karr, Abhishek Banerjee, and Punyasloka Mishra:
Solving an Inverse Partial Differential Equation for a Two Dimensional Heat Conduction Problem with Oscillating Boundary Conditions Using an Artificial Immune System

Hai Qiu and Jay Lee:
Feature Fusion and Degradation Detection Using Self-organizing Map ( SOM)

Session 4:

Support Vector Machines

Session Chair:
Bernd-Juergen Falkowski

183 , 168 , 150 , 131, 174, 128

Mikhail Petrovskiy:
A Game Theory Approach to Pairwise Classification with Support Vector Machines

Adam H. Cannon, Don Hush:
Multiple Instance Learning Using Simple Classifiers

Nicola Ancona, Rosalie Maglietta, and Ettore Stella:
Sparse representations and performances in Support Vector Machines

Bernd-Juergen Falkowski:
Scoring Systems, Classifiers, Default Probabilities, and Kernel Methods

Alina Lazar:
Income Prediction via Support Vector Machine

Tood Blank, Leen-Kiat Soh, Stephen Scott:
Creating an SVM to Play Strong Poker


Coffee Break


Session 5:

Applications - 2

Session Chair:
Olfa Nasraoui

171 , 132, 153

Gregory Von Pless, Tayeb Al Larim, and  Leonid Reznik:<
Time-Based Multi-Layer Perceptron for Novelty Detection in Sensor Networks

Durga Toshniwal and Ramesh Chandra Joshi:
Similarity Search in Time Series Databases Using Moments

Rafael Ramirez, A. Hazan:
Induction of Expressive Music Performance Models

Vladimir Shlain:
Basic Algorithms of Automatic Defect Classification System for Inspection Tools in Semiconductor Industry

Session 6:

Machine Learning Techniques - 2

Session Chair:
Joost Broekens

175 , 165A , 127 , 140, 169

Daren Ler, Irena Koprinska, Sanjay Chawla:
A new Landmarker Generation Algorithm Based on Correlativity

Wayne Staats, Marwa Shideed, and S. Lu:
An Adaptive Approach For Assisting In the Recovery From Spatial Disorientation

Stephen D. Scott:
Agnostic Learning of General Geometric Patterns and Multí-instance Learning in Yd

Peter Géczy and Shiro Usui:
Effective Dynamic Sample Selection Algorithm

Joost Broekens and Doug DeGroot:
Emergent Representation and Reasoning in Adaptive Agents

7:00 – 9:00

ICMLA’04 Conference Reception

Friday, December 17, 2004


Conference Room 1

Conference Room 2




Session 7:

Applications - 3

Session Chair:
Jonathan Deming

101 , 182 , 147 , 102

Jonathan Deming and Stephen Bruder:
Obstacle Avoidance Using Image Flow in an RT-Linux Environment on a PC-104 Platform

Karl Torkkola, Noel Massey, Chip Wood:
Detecting Driver Inattention in the Absence of Driver Monitoring Sensors

John H. Lilly:
Evolution of a P/N Fuzzy Obstacle Avoidance Controller for an Autonomous Robot

Jonathan R. Deming and Marco A. A. deOliveira:
Autonomous Navigation Using Neural Networks

Session 8:

Data Mining Techniques - 1

Session Chair:

Lukasz Kurgan

185 , 190 , 187 , 151

Lukasz A. Kurgan:
Reducing Complexity of Rule Based Models via Meta Mining

Jonatan Gomez, Olfa Nasraoui, and Elizabeth Leon:
RAIN: Data Clustering using Randomized Interactions between Data Points

Anup Kumar, Mehmed Kantardzic, Padmanabhan Ramaswamy, Pedram Sadeghian:
An Extensible Service Oriented Distributed Data Mining Framework

Manimozhiyan Arumugam and Stephen D. Scott:
EMPRR: A High-Dimensional EM-Based Piecewise Regression Algorithm


Coffee Break


Session 9:

Classification and Prediction

Session Chair:
Roseli A. F. Romero

181 , 121 , 163 , 141, 100

Iryna Skrypnyk:
Exploring Classification Heterogeneity with IPA

Danyu Liu , Alan P. Sprague, Jeffrey G. Gray:
PolyCluster: An Interactive Visualization Approach to Construct Classification Rules

Patricia R. Oliveira and Roseli A. F. Romero:
Enhanced ICA Mixture Model for Image Segmentation

Jufen Zhang and Richard Everson:
Bayesian Estimation and Classification with Incomplete data Using Mixture Models

Michael James, S. Singh, M. L. Littman:
Planning with Predictive State Representations

Session 10:

Association Rules

Session Chair:
Lawrence Mazlack

120 , 180 , 173 , 154A , 138

Lawrence J. Mazlack:
Using Association Rules Without Understanding Their Underlying Causality Reduces Their Decision Value

Behrouz Minaei-Bidgoli, Pang-Ning Tan, and William F. Punch:
Mining Interesting Contrast Rules for a Web-based Educational System

Huaiguo Fu, Engelbert Mephu Nguifo:
Mining Frequent Closed Itemsets for Large Data

Rafiqul Islam, Safwan Mahmud Khan at al.:
A Comparative Study among Three Algorithms for Frequent Pattern Generation

Alan P. Sprague:
On the Computational Complexity of Two Frequent Set Generation Algorithms


Lunch Break


Special Session:

Biomedical Applications 1

Session Chair:
Georgia D. Tourassi

191 , 161 , 162 , 184,

Mia K. Markey and Amit Patel:
Impact of Missing Data in Training Artificial Neural Networks for Computer Aided Diagnosis

Adam Gaweda, A. A. Jakobs, G. R. Aronoff, M. E. Brier:
Intelligent Control for Drug Delivery in Management of Renal Anemia

Yafeng Hou, Jacek M. Zurada, and Waldemar Karwowski:
Prediction of Dynamic Forces on Lumbar Joint Using a Recurrent Neural Network Model

Pallavi Vyas, Adel Elmaghraby, Robert Topp:
Data Mining Application for Predictive Learning from Visiting Nurse Association Data


Coffee Break


Special Session:

Biomedical Applications 2

Session Chair:
M. Arif Wani

166 , 164 , 159, 154B

F.-M. Schleif, U. Clauss, T. Villmann and B. Hammer:
Supervised Relevance Neural Gas and Unified Maximum Separability Analysis for Classification of Mass Spectrometric Data

Kreshna Gopal at al.:
Efficient Retrieval of Electron Density Patterns for Modeling Proteins by X-ray Crystallography

Bram Vanschoenwinkel, Bernard Manderick:
Substitution Matrix based Kernel for Protein Secondary Structure Prediction

Safwan Mahmud Khan, R. Islam, M. U. Chowdhury:
Medical Image Classification Using an Efficient Data Mining Technique


ICMLA’04 Conference Dinner

Saturday, December 18, 2004


Conference Room 1

Conference Room 2




Session 11:

Applications - 4

Session Chair:
Leen-Kiat Soh

114 , 112 , 110 , 134

Mircea Gh. Negoita and David Pritchard:
A “Virtual Student” Leads to the Possibility Of Optimiser Agents in an ITS

Joseph Bernadt, Leen-Kiat Soh :
Authoritative Citation KNN Learning
in Multiple-Instance Problems

Oystein Hernes and Jianna J. Zhang :
A Tutorial Search Engine Based on
Bayesian Learning

Todd Blank, L. Soh, L. D. Miller, S. Person:
Case-Based Learning Mechanisms to Deliver Learning Materials

Session 12:

Data Mining Techniques - 2

Session Chair:
Alan P. Sprague

179 , 160 , 158 , 126

Choh Man Teng:
Coping with Partially Corrupted Data

Ying Liu, Alan P. Sprague:
Outlier Detection and Evaluation by Network Flow

EunSang  Bak:
Data Augmentation for Linearly Separable Feature Space

Christopher K. Monson, D. Wingate, T. S. Peterson:
Variable Resolution Discretization in the Joint Space


Coffee Break


Session 13:

Machine Learning @ Soft Computing

Session Chair:
Key Ho Kwon

106 , 108 , 156, 155

R. Rastegar, M. R. Meybodi, K. Badie:
A New Discrete Binary Particle Swarm Optimization based on Learning Automata

Key Ho Kwon and A. T. Alouani:
Implementation of Parallel GAs in Conjunction with Fuzzy Algorithm

Abdul MajidA. Khan, A. M. Mirza:
Improving the Performance of NN Classifier Using Genetic Programming

Binto George and Susan S. Mathai:
Improving Quality of Inference in Multilevel Secure Knowledge-Based Systems


Closing Session

Chair: Mehmed Kantardzic

Best Paper Award Announcement