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ICMLA 2007: Cincinnati, Ohio, USA
- M. Arif Wani, Mehmed M. Kantardzic, Tao Li, Ying Liu, Lukasz A. Kurgan, Jieping Ye, Mitsunori Ogihara, Seref Sagiroglu, Xue-wen Chen, Leif E. Peterson, Khalid Hafeez:
The Sixth International Conference on Machine Learning and Applications, ICMLA 2007, Cincinnati, Ohio, USA, 13-15 December 2007. IEEE Computer Society 2008, ISBN 0-7695-3069-9
Invited Speakers
- William W. Cohen:
Machine Learning for Information Management: Some Promising Directions. - Eric P. Xing:
Probabilistic Graphical Models-Theory, Algorithm, and Application. - Pierre Baldi:
Machine Learning Challenges in Chemoinformatics and Drug Screening and Design. - Shamkant B. Navathe:
Text Mining and Ontology Applications in Bioinformatics and GIS. - Jacek M. Zurada:
Neural Networks with Complex-Valued Neurons for Recurrent and Feedforward Architectures. - Brendan J. Frey:
Learning in Biomedicine and Bioinformatics Using Affinity Propagation. - Bernd Wachmann:
Technologies and Solutions for Trend Detection in Public Literature for Biomarker Discovery.
Support Vector Machines
- Yulin Dong, Manghui Tu, Zhonghang Xia, Guangming Xing:
An optimization method for selecting parameters in support vector machines. 1-6 - Thanh-Nghi Do, Jean-Daniel Fekete:
Large Scale Classification with Support Vector Machine Algorithms. 7-12 - Martin Renqiang Min, Anthony J. Bonner, Zhaolei Zhang:
Modifying kernels using label information improves SVM classification performance. 13-18 - Laura Diosan, Alexandrina Rogozan, Jean-Pierre Pécuchet:
Evolving kernel functions for SVMs by genetic programming. 19-24 - Gilles Gasso, Karina Zapien Arreola, Stéphane Canu:
Sparsity regularization path for semi-supervised SVM. 25-30
Evolutionary Methods
- Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Nelson:
Improving gene expression programming performance by using differential evolution. 31-37 - Amin Shali, Mohammad Reza Kangavari, Bahareh Bina:
Using genetic programming for the induction of oblique decision trees. 38-43 - Michiyuki Hirokane, Shusaku Kouno, Yasutoshi Nomura:
Extraction of minimum decision algorithm using rough sets and genetic algorithms. 44-49 - Guillaume Jouffroy:
Design of Simple Limit Cycles with Recurrent Neural Networks for Oscillatory Control. 50-55 - Ting Qian:
Multi-Stages Genetic Algorithms: Introducing Temporal Structures to Facilitate Selection of Optimal Evolutionary Paths. 56-61 - QingBao Zhu, Shuyan Chen:
A New Ant Evolution Algorithm to Resolve TSP Problem. 62-66
Data Mining
- Haiyun Bian, Raj Bhatnagar, Barrington Young:
An Efficient Constraint-Based Closed Set Mining Algorithm. 67-72 - Mehdi Adda
, Lei Wu, Yi Feng:
Rare Itemset Mining. 73-80 - P. Santhi Thilagam
Semantic Partition Based Association Rule Mining across Multiple Databases Using Abstraction. 81-86 - Claudio Haruo Yamamoto, Maria Cristina Ferreira de Oliveira
An Itemset-Driven Cluster-Oriented Approach to Extract Compact and Meaningful Sets of Association Rules. 87-92 - Dadong Yu, Dongbo Liu, Rui Luo, Jianxin Wang:
Clustering Categorical Data Based on Maximal Frequent Itemsets. 93-97
Learning
- Neetha Sebastian, Kamala Krithivasan:
Learning Algorithms for Grammars of Variable Arity Trees. 98-103 - Jason Bobbin:
An incremental viterbi algorithm. 104-111 - Érick Alphonse, Aomar Osmani:
Phase transition and heuristic search in relational learning. 112-117 - Cristina Boicu, Gheorghe Tecuci, Mihai Boicu:
Learning complex problem solving expertise from failures. 118-123 - Guillaume Bouchard:
Bias-variance tradeoff in hybrid generative-discriminative models. 124-129
Text and Multimedia Learning
- Catarina Silva
Combining active learning and relevance vector machines for text classification. 130-135 - Fei Wang, Xin Wang, Tao Li:
Efficient label propagation for interactive image segmentation. 136-141 - Jia Tse, Christopher Jones, Dean Curtis, Evangelos A. Yfantis:
An OCR-independent character segmentation using shortest-path in grayscale document images. 142-147 - Somnath Banerjee:
Boosting inductive transfer for text classification using wikipedia. 148-153 - Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Ismail, William A. Wallace:
Discover the power of social and hidden curriculum to decision making: experiments with enron email and movie newsgroups. 154-159
Application I
- Guillaume Bouchard, Jean-Marc Andreoli:
Soft Failure Detection Using Factorial Hidden Markov Models. 160-165 - Andrew Carlson, Ian Fette:
Memory-based context-sensitive spelling correction at web scale. 166-171 - Barrington Young, Raj Bhatnagar, Giridhar Tatavarty, Haiyun Bian:
Covariance matrix computations with federated databases. 172-177 - André Stuhlsatz:
Recognition of ultrasonic multi-echo sequences for autonomous symbolic indoor tracking. 178-185
Learning
- Toshiyuki Sueyoshi, Gopalakrishna Reddy Tadiparthi:
An agent based system for california electricity market: a perspective of myopic machine learning. 186-191 - Shawn Martin, Sean McKenna:
Predicting building contamination using machine learning. 192-197 - Martin Schierle, Sascha Schulz:
Bootstrapping algorithms for an application in the automotive domain. 198-203
Classification
- Lofton A. Bullard, Taghi M. Khoshgoftaar, Kehan Gao:
An application of a rule-based model in software quality classification. 204-210 - Henrik Boström:
Estimating class probabilities in random forests. 211-216 - Robert H. Fujii, Taiki Ichishita:
Effect of synaptic weight assignment on spiking neuron response. 217-222
Application II
- Dianwei Han, Jun Zhang:
A comparison of two algorithms for predicting the condition number. 223-228 - Thomas J. Mitchell, David P. Creasey:
Evolutionary Sound Matching: A Test Methodology and Comparative Study. 229-234 - Slawomir Nowaczyk
Learning to evaluate conditional partial plans. 235-240
Regression/Prediction
- Balaji Kommineni, Shubhankar Basu, Ranga Vemuri:
A spline based regression technique on interval valued noisy data. 241-247 - Yang Lan, Daniel Neagu
A new time series prediction algorithm based on moving average of nth-order difference. 248-253 - David Thornley, Maxim Zverev, Stavros Petridis:
Machine learned regression for abductive DNA sequencing. 254-259 - Jian-Wu Xu, Shipeng Yu, Jinbo Bi, Lucian Vlad Lita, Radu Stefan Niculescu, R. Bharat Rao:
Automatic medical coding of patient records via weighted ridge regression. 260-265 - Adeline Schmitz, Hamid Hefazi:
Constructive neural network ensemble for regression tasks in high dimensional spaces. 266-273
Machine Learning in Web Based Real-Time Applications
- Nihat Yilmaz, Seref Sagiroglu:
Web-based maze robot learning using fuzzy motion control system. 274-279 - Seref Sagiroglu, Uraz Yavanoglu, Esra Nergis Guven:
Web based machine learning for language identification and translation. 280-285 - Hamdi Tolga Kahraman
A web based adaptive educational system. 286-291
Dimensionality Reduction
- Michael Davy, Saturnino Luz:
Dimensionality reduction for active learning with nearest neighbour classifier in text categorisation problems. 292-297 - Yiming Wu, Xiuwen Liu, Washington Mio:
Scalable optimal linear representation for face and object recognition. 298-303
Induction, Model Selection and Evaluation
- Chunsheng Yang, Sylvain Létourneau:
Model evaluation for prognostics: estimating cost saving for the end users. 304-309 - Jung Min Kong, Dong-Hun Seo, Won Don Lee:
Rule refinement with extended data expression. 310-315 - Guénaël Cabanes
A simultaneous two-level clustering algorithm for automatic model selection. 316-321 - Peter Owotoki
LEONARDO - The computational intelligence (CI) model selection wizard. 322-329 - José A. Ramírez-Hernández, Emmanuel Fernandez:
Control of a re-entrant line manufacturing model with a reinforcement learning approach. 330-335
Reinforcement Learning/ Learning from Imbalanced Data/Bayesian Networks
- Víctor Uc Cetina
Supervised reinforcement learning using behavior models. 336-341 - Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, Frank Kirchner:
Performance evaluation of EANT in the robocup keepaway benchmark. 342-347 - Taghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse, Amri Napolitano, Andres Folleco:
Learning with limited minority class data. 348-353 - Manuel Stritt, Lars Schmidt-Thieme, Gerhard Poeppel:
Combining multi-distributed mixture models and bayesian networks for semi-supervised learning. 354-362 - Dennis J. Drown, Taghi M. Khoshgoftaar, Ramaswamy Narayanan:
Using evolutionary sampling to mine imbalanced data. 363-368 - Alexandra M. Carvalho, Arlindo L. Oliveira:
Learning bayesian networks consistent with the optimal branching. 369-374
Unsupervised Learning
- Qiyong Guo, Hongyu Li, Wenbin Chen
Manifold clustering via energy minimization. 375-380 - Jian Zhang:
Co-clustering by similarity refinement. 381-386 - Thouraya Ayadi, Tarek M. Hamdani
2IBGSOM: interior and irregular boundaries growing self-organizing maps. 387-392 - Bülent Yücesoy, Sule Gündüz Ögüdücü:
Comparison of semantic and single term similarity measures for clustering turkish documents. 393-398 - Dong Moon Kim, Kunsu Kim, Kyo-Hyun Park, Jee-Hyong Lee, Keon-Myung Lee
A music recommendation system with a dynamic k-means clustering algorithm. 399-403
Feature Extraction and Selection / Ensemble Learning
- Sasthakumar Ramamurthy, Raj Bhatnagar:
Tracking recurrent concept drift in streaming data using ensemble classifiers. 404-409 - Viktoria Rojkova, Mehmed M. Kantardzic:
Feature extraction using random matrix theory approach. 410-416 - Lei Yu, Hao Li:
Toward optimal selection of feature clusters. 417-422 - Dean Curtis, Vitaliy Kubushyn, Evangelos A. Yfantis, Michael Rogers:
A hierarchical feature decomposition clustering algorithm for unsupervised classification of document image types. 423-428 - Xue-wen Chen, Jong Cheol Jeong:
Enhanced recursive feature elimination. 429-435
Application III
- Johannes Hartz, Bernd Neumann:
Learning a knowledge base of ontological concepts for high-level scene interpretation. 436-443 - Bo Li, Juan Liu, Wenjuan Shi:
Web-based parallel corpora for statistical machine translation. 444-449 - Volker Willert, Marc Toussaint, Julian Eggert, Edgar Körner:
Uncertainty optimization for robust dynamic optical flow estimation. 450-457 - Brian Burford:
Direct calculation of predictions for K29/K29. 458-463 - Mehdi Samadi, Zohreh Azimifar, Mansoor Zolghadri Jahromi
Learning: An Effective Approach in Endgame Chess Board Evaluation. 464-469 - Mohmad Marouf Wani, M. Arif Wani:
Hybrid Neural Network Based Model for Predicting the Performance of a Two Stroke Spark Ignition Engine. 470-475
Machine Learning Applications in Bioinformatics
- Yi Sun, Mark Robinson, Rod Adams, Neil Davey, Alistair G. Rust:
Predicting Binding Sites in the Mouse Genome. 476-481 - Glenn Fung, Renaud Seigneuric, Sriram Krishnan, R. Bharat Rao, Brad G. Wouters
Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in Cancer. 482-487 - Michalis E. Blazadonakis, Michalis E. Zervakis:
Polynomial and RBF Kernels as Marker Selection Tools-A Breast Cancer Case Study. 488-493 - Daniele Yumi Sunaga, Júlio C. Nievola, Milton Pires Ramos:
Statistical and Biological Validation Methods in Cluster Analysis of Gene Expression. 494-499 - Bobbie-Jo M. Webb-Robertson, Christopher S. Oehmen, William R. Cannon:
Support Vector Machine Classification of Probability Models and Peptide Features for Improved Peptide Identification from Shotgun Proteomics. 500-505 - Amit U. Sinha, Mukta Phatak, Raj Bhatnagar, Anil G. Jegga
Identifying Functional Binding Motifs of Tumor Protein p53 Using Support Vector Machines. 506-511
Workshop Session: Machine Learning Applications in Biomedicine
- Claire L. McCullough, Andrew J. Novobilski, Francis M. Fesmire:
Use of Neural Networks to Predict Adverse Outcomes from Acute Coronary Syndrome for Male and Female Patients. 512-517 - Janusz Wojtusiak, Ryszard S. Michalski, Thipkesone Simanivanh, Anna V. Baranova:
The Natural Induction System AQ21 and its Application to Data Describing Patients with Metabolic Syndrome: Initial Results. 518-523 - Sang-Chul Lee, Peter Bajcsy:
Understanding Challenges in Preserving and Reconstructing Computer-Assisted Medical Decision Processes. 524-529 - Rómer Rosales, Praveen Krishnamurthy, R. Bharat Rao:
Semi-Supervised Active Learning for Modeling Medical Concepts from Free Text. 530-536 - Alexander Senf
A Statistical Algorithm to Discover Knowledge in Medical Data Sources. 537-540 - Kai Xing, Donald Henson, Dechang Chen, Li Sheng:
A Clustering-Based Approach to Predict Outcome in Cancer Patients. 541-546
Workshop Session: Machine Learning Applications in Genomics
- Mingzhou (Joe) Song
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming. 547-553 - Kwangmin Choi, Youngik Yang, Sun Kim:
CLASSEQ: Classification of Sequences via Comparative Analysis of Multiple Genomes. 554-559 - Li Chen, Chen Wang, Ie-Ming Shih, Tian-Li Wang, Zhen Zhang, Yue Joseph Wang, Robert Clarke, Eric P. Hoffman, Jianhua Xuan:
Biomarker Identification by Knowledge-Driven Multi-Level ICA and Motif Analysis. 560-566 - Dietmar H. Dorr, Anne Denton:
Generalized Sequence Signatures through Symbolic Clustering. 567-572 - Mark A. Kon, Yue Fan, Dustin T. Holloway, Charles DeLisi:
SVMotif: A Machine Learning Motif Algorithm. 573-580
Workshop Session: Machine Learning Applications in Proteomics
- Thomas Villmann, Frank-Michael Schleif
Association Learning in SOMs for Fuzzy-Classification. 581-586 - Ronald C. Taylor
SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network Reconstruction. 587-593 - Jia Song, Chunmei Liu, Yinglei Song, Junfeng Qu:
Alignment of Multiple Proteins with an Ensemble of Hidden Markov Models. 594-599 - Dongxiao Zhu, Hua Li:
Improvement of Bayesian Network Inference Using a Relaxed Gene Ordering. 600-605
Workshop Session: Machine Learning Applications in Transcriptomics
- Young-Rae Cho, Xian Xu, Woochang Hwang, Aidong Zhang:
Feature Extraction from Microarray Expression Data by Integration of Semantic Knowledge. 606-611 - Huilin Xiong, Ya Zhang, Xue-wen Chen:
Normalized Linear Transform for Cross-Platform Microarray Data Integration. 612-617 - Leif E. Peterson, Matthew A. Coleman:
Logistic Ensembles for Random Spherical Linear Oracles. 618-623 - Zhenqiu Liu:
Cox's Proportional Hazards Model with Lp Penalty for Biomarker Identification and Survival Prediction. 624-628 - Lynne Billard, Duck-Ki Kim, Chan-Hee Lee, Sung Duck Lee, Keon-Myung Lee
Modeling Spatial-Temporal Epidemics Using STBL Model. 629-633
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