Table of Contents

• Machine Learning for Information Management: Some Promising DirectionsWilliam W. Cohen. [doi]
• Text Mining and Ontology Applications in Bioinformatics and GISShamkant B. Navathe. [doi]
• Probabilistic Graphical Models-Theory, Algorithm, and ApplicationEric P. Xing. [doi]
• Neural Networks with Complex-Valued Neurons for Recurrent and Feedforward ArchitecturesJacek M. Zurada. [doi]
• Learning in Biomedicine and Bioinformatics Using Affinity PropagationBrendan J. Frey. [doi]
• Technologies and Solutions for Trend Detection in Public Literature for Biomarker DiscoveryBernd Wachmann. [doi]
• Machine Learning Challenges in Chemoinformatics and Drug Screening and DesignPierre Baldi. [doi]
• An optimization method for selecting parameters in support vector machinesYulin Dong, Manghui Tu, Zhonghang Xia, Guangming Xing. 1-6 [doi]
• Large Scale Classification with Support Vector Machine AlgorithmsThanh-Nghi Do, Jean-Daniel Fekete. 7-12 [doi]
• Modifying kernels using label information improves SVM classification performanceMartin Renqiang Min, Anthony J. Bonner, Zhaolei Zhang. 13-18 [doi]
• Evolving kernel functions for SVMs by genetic programmingLaura Diosan, Alexandrina Rogozan, Jean-Pierre Pécuchet. 19-24 [doi]
• Sparsity regularization path for semi-supervised SVMGilles Gasso, Karina Zapien Arreola, Stéphane Canu. 25-30 [doi]
• Improving gene expression programming performance by using differential evolutionQiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Nelson. 31-37 [doi]
• Using genetic programming for the induction of oblique decision treesAmin Shali, Mohammad Reza Kangavari, Bahareh Bina. 38-43 [doi]
• Extraction of minimum decision algorithm using rough sets and genetic algorithmsMichiyuki Hirokane, Shusaku Kouno, Yasutoshi Nomura. 44-49 [doi]
• Design of Simple Limit Cycles with Recurrent Neural Networks for Oscillatory ControlGuillaume Jouffroy. 50-55 [doi]
• Multi-Stages Genetic Algorithms: Introducing Temporal Structures to Facilitate Selection of Optimal Evolutionary PathsTing Qian. 56-61 [doi]
• A New Ant Evolution Algorithm to Resolve TSP ProblemQingBao Zhu, Shuyan Chen. 62-66 [doi]
• An Efficient Constraint-Based Closed Set Mining AlgorithmHaiyun Bian, Raj Bhatnagar, Barrington Young. 67-72 [doi]
• Rare Itemset MiningMehdi Adda, Lei Wu, Yi Feng. 73-80 [doi]
• Semantic Partition Based Association Rule Mining across Multiple Databases Using AbstractionP. Santhi Thilagam, V. S. Ananthanarayana. 81-86 [doi]
• An Itemset-Driven Cluster-Oriented Approach to Extract Compact and Meaningful Sets of Association RulesClaudio Haruo Yamamoto, Maria Cristina Ferreira de Oliveira, Magaly Lika Fujimoto, Solange Oliveira Rezende. 87-92 [doi]
• Clustering Categorical Data Based on Maximal Frequent ItemsetsDadong Yu, Dongbo Liu, Rui Luo, Jianxin Wang. 93-97 [doi]
• Learning Algorithms for Grammars of Variable Arity TreesNeetha Sebastian, Kamala Krithivasan. 98-103 [doi]
• An incremental viterbi algorithmJason Bobbin. 104-111 [doi]
• Phase transition and heuristic search in relational learningÉrick Alphonse, Aomar Osmani. 112-117 [doi]
• Learning complex problem solving expertise from failuresCristina Boicu, Gheorghe Tecuci, Mihai Boicu. 118-123 [doi]
• Bias-variance tradeoff in hybrid generative-discriminative modelsGuillaume Bouchard. 124-129 [doi]
• Combining active learning and relevance vector machines for text classificationCatarina Silva, Bernardete Ribeiro. 130-135 [doi]
• Efficient label propagation for interactive image segmentationFei Wang, Xin Wang, Tao Li. 136-141 [doi]
• An OCR-independent character segmentation using shortest-path in grayscale document imagesJia Tse, Christopher Jones, Dean Curtis, Evangelos A. Yfantis. 142-147 [doi]
• Boosting inductive transfer for text classification using wikipediaSomnath Banerjee. 148-153 [doi]
• Discover the power of social and hidden curriculum to decision making: experiments with enron email and movie newsgroupsHung-Ching Chen, Mark K. Goldberg, Malik Magdon-Ismail, William A. Wallace. 154-159 [doi]
• Soft Failure Detection Using Factorial Hidden Markov ModelsGuillaume Bouchard, Jean-Marc Andreoli. 160-165 [doi]
• Memory-based context-sensitive spelling correction at web scaleAndrew Carlson, Ian Fette. 166-171 [doi]
• Covariance matrix computations with federated databasesBarrington Young, Raj Bhatnagar, Giridhar Tatavarty, Haiyun Bian. 172-177 [doi]
• Recognition of ultrasonic multi-echo sequences for autonomous symbolic indoor trackingAndré Stuhlsatz. 178-185 [doi]
• An agent based system for california electricity market: a perspective of myopic machine learningToshiyuki Sueyoshi, Gopalakrishna Reddy Tadiparthi. 186-191 [doi]
• Predicting building contamination using machine learningShawn Martin, Sean McKenna. 192-197 [doi]
• Bootstrapping algorithms for an application in the automotive domainMartin Schierle, Sascha Schulz. 198-203 [doi]
• An application of a rule-based model in software quality classificationLofton A. Bullard, Taghi M. Khoshgoftaar, Kehan Gao. 204-210 [doi]
• Estimating class probabilities in random forestsHenrik Boström. 211-216 [doi]
• Effect of synaptic weight assignment on spiking neuron responseRobert H. Fujii, Taiki Ichishita. 217-222 [doi]
• A comparison of two algorithms for predicting the condition numberDianwei Han, Jun Zhang. 223-228 [doi]
• Evolutionary Sound Matching: A Test Methodology and Comparative StudyThomas J. Mitchell, David P. Creasey. 229-234 [doi]
• Learning to evaluate conditional partial plansSlawomir Nowaczyk, Jacek Malec. 235-240 [doi]
• A spline based regression technique on interval valued noisy dataBalaji Kommineni, Shubhankar Basu, Ranga Vemuri. 241-247 [doi]
• A new time series prediction algorithm based on moving average of nth-order differenceYang Lan, Daniel Neagu. 248-253 [doi]
• Machine learned regression for abductive DNA sequencingDavid Thornley, Maxim Zverev, Stavros Petridis. 254-259 [doi]
• Automatic medical coding of patient records via weighted ridge regressionJian-Wu Xu, Shipeng Yu, Jinbo Bi, Lucian Vlad Lita, Radu Stefan Niculescu, R. Bharat Rao. 260-265 [doi]
• Constructive neural network ensemble for regression tasks in high dimensional spacesAdeline Schmitz, Hamid Hefazi. 266-273 [doi]
• Web-based maze robot learning using fuzzy motion control systemNihat Yilmaz, Seref Sagiroglu. 274-279 [doi]
• Web based machine learning for language identification and translationSeref Sagiroglu, Uraz Yavanoglu, Esra Nergis Guven. 280-285 [doi]
• A web based adaptive educational systemHamdi Tolga Kahraman, Ilhami Colak, Seref Sagiroglu. 286-291 [doi]
• Dimensionality reduction for active learning with nearest neighbour classifier in text categorisation problemsMichael Davy, Saturnino Luz. 292-297 [doi]
• Scalable optimal linear representation for face and object recognitionYiming Wu, Xiuwen Liu, Washington Mio. 298-303 [doi]
• Model evaluation for prognostics: estimating cost saving for the end usersChunsheng Yang, Sylvain Létourneau. 304-309 [doi]
• Rule refinement with extended data expressionJung Min Kong, Dong-Hun Seo, Won Don Lee. 310-315 [doi]
• A simultaneous two-level clustering algorithm for automatic model selectionGuénaël Cabanes, Younès Bennani. 316-321 [doi]
• LEONARDO - The computational intelligence (CI) model selection wizardPeter Owotoki, Friedrich Mayer-Lindenberg. 322-329 [doi]
• Control of a re-entrant line manufacturing model with a reinforcement learning approachJosé A. Ramírez-Hernández, Emmanuel Fernandez. 330-335 [doi]
• Supervised reinforcement learning using behavior modelsVictor Uc Cetina. 336-341 [doi]
• Performance evaluation of EANT in the robocup keepaway benchmarkJan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, Frank Kirchner. 342-347 [doi]
• Learning with limited minority class dataTaghi M. Khoshgoftaar, Chris Seiffert, Jason Van Hulse, Amri Napolitano, Andres Folleco. 348-353 [doi]
• Combining multi-distributed mixture models and bayesian networks for semi-supervised learningManuel Stritt, Lars Schmidt-Thieme, Gerhard Poeppel. 354-362 [doi]
• Using evolutionary sampling to mine imbalanced dataDennis J. Drown, Taghi M. Khoshgoftaar, Ramaswamy Narayanan. 363-368 [doi]
• Learning bayesian networks consistent with the optimal branchingAlexandra M. Carvalho, Arlindo L. Oliveira. 369-374 [doi]
• Manifold clustering via energy minimizationQiyong Guo, HongYu Li, Wenbin Chen, I-Fan Shen, Jussi Parkkinen. 375-380 [doi]
• Co-clustering by similarity refinementJian Zhang. 381-386 [doi]
• 2IBGSOM: interior and irregular boundaries growing self-organizing mapsThouraya Ayadi, Tarek M. Hamdani, Adel M. Alimi, Mohamed A. Khabou. 387-392 [doi]
• Comparison of semantic and single term similarity measures for clustering turkish documentsBülent Yücesoy, Sule Gündüz Ögüdücü. 393-398 [doi]
• A music recommendation system with a dynamic k-means clustering algorithmDong Moon Kim, Kunsu Kim, Kyo-hyun Park, Jee-Hyong Lee, Keon-Myung Lee. 399-403 [doi]
• Tracking recurrent concept drift in streaming data using ensemble classifiersSasthakumar Ramamurthy, Raj Bhatnagar. 404-409 [doi]
• Feature extraction using random matrix theory approachViktoria Rojkova, Mehmed M. Kantardzic. 410-416 [doi]
• Toward optimal selection of feature clustersLei Yu, Hao Li. 417-422 [doi]
• A hierarchical feature decomposition clustering algorithm for unsupervised classification of document image typesDean Curtis, Vitaliy Kubushyn, Evangelos A. Yfantis, Michael Rogers. 423-428 [doi]
• Enhanced recursive feature eliminationXue-wen Chen, Jong Cheol Jeong. 429-435 [doi]
• Learning a knowledge base of ontological concepts for high-level scene interpretationJohannes Hartz, Bernd Neumann. 436-443 [doi]
• Web-based parallel corpora for statistical machine translationBo Li, Juan Liu, Wenjuan Shi. 444-449 [doi]
• Uncertainty optimization for robust dynamic optical flow estimationVolker Willert, Marc Toussaint, Julian Eggert, Edgar Körner. 450-457 [doi]
• Direct calculation of predictions for K29/K29Brian Burford. 458-463 [doi]
• Learning: An Effective Approach in Endgame Chess Board EvaluationMehdi Samadi, Zohreh Azimifar, Mansour Zolghadri Jahromi. 464-469 [doi]
• Hybrid Neural Network Based Model for Predicting the Performance of a Two Stroke Spark Ignition EngineMohmad Marouf Wani, M. Arif Wani. 470-475 [doi]
• Predicting Binding Sites in the Mouse GenomeYi Sun, Mark Robinson, Rod Adams, Neil Davey, Alistair G. Rust. 476-481 [doi]
• Reducing a Biomarkers List via Mathematical Programming: Application to Gene Signatures to Detect Time-Dependent Hypoxia in CancerGlenn Fung, Renaud. Seigneuric, Sriram Krishnan, R. Bharat Rao, Brad G. Wouters, Philippe Lambin. 482-487 [doi]
• Polynomial and RBF Kernels as Marker Selection Tools-A Breast Cancer Case StudyMichalis E. Blazadonakis, Michalis E. Zervakis. 488-493 [doi]
• Statistical and Biological Validation Methods in Cluster Analysis of Gene ExpressionDaniele Yumi Sunaga, Júlio C. Nievola, Milton Pires Ramos. 494-499 [doi]
• Support Vector Machine Classification of Probability Models and Peptide Features for Improved Peptide Identification from Shotgun ProteomicsBobbie-Jo M. Webb-Robertson, Christopher S. Oehmen, William R. Cannon. 500-505 [doi]
• Identifying Functional Binding Motifs of Tumor Protein p53 Using Support Vector MachinesAmit U. Sinha, Mukta Phatak, Raj Bhatnagar, Anil G. Jegga. 506-511 [doi]
• Use of Neural Networks to Predict Adverse Outcomes from Acute Coronary Syndrome for Male and Female PatientsClaire L. McCullough, Andrew J. Novobilski, Francis M. Fesmire. 512-517 [doi]
• The Natural Induction System AQ21 and its Application to Data Describing Patients with Metabolic Syndrome: Initial ResultsJanusz Wojtusiak, Ryszard S. Michalski, Thipkesone Simanivanh, Anna V. Baranova. 518-523 [doi]
• Understanding Challenges in Preserving and Reconstructing Computer-Assisted Medical Decision ProcessesSang-Chul Lee, Peter Bajcsy. 524-529 [doi]
• Semi-Supervised Active Learning for Modeling Medical Concepts from Free TextRómer Rosales, Praveen Krishnamurthy, R. Bharat Rao. 530-536 [doi]
• A Statistical Algorithm to Discover Knowledge in Medical Data SourcesAlexander J. Senf, Carl Leonard, James M. DeLeo. 537-540 [doi]
• A Clustering-Based Approach to Predict Outcome in Cancer PatientsKai Xing, Donald Henson, Dechang Chen, Li Sheng. 541-546 [doi]
• Maximum Likelihood Quantization of Genomic Features Using Dynamic ProgrammingMingzhou (Joe) Song, Robert M. Haralick, Stéphane Boissinot. 547-553 [doi]
• CLASSEQ: Classification of Sequences via Comparative Analysis of Multiple GenomesKwangmin Choi, Youngik Yang, Sun Kim. 554-559 [doi]
• Biomarker Identification by Knowledge-Driven Multi-Level ICA and Motif AnalysisLi Chen, Chen Wang, Le-Ming Shih, Tian-Li Wang, Zhen Zhang, Yue Wang, Robert Clarke, Eric Hoffman, Jianhua Xuan. 560-566 [doi]
• Generalized Sequence Signatures through Symbolic ClusteringDietmar H. Dorr, Anne Denton. 567-572 [doi]
• SVMotif: A Machine Learning Motif AlgorithmMark A. Kon, Yue Fan, Dustin T. Holloway, Charles DeLisi. 573-580 [doi]
• Association Learning in SOMs for Fuzzy-ClassificationThomas Villmann, Frank-Michael Schleif, Martijn van der Werff, André M. Deelder, Rob A. E. M. Tollenaar. 581-586 [doi]
• SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network ReconstructionRonald C. Taylor, Mudita Singhal, Don Simone Daly, Kelly Domico, Amanda M. White, Deanna L. Auberry, Kenneth J. Auberry, Brian Hooker, Gregory B. Hurst, Jason McDermott, W. Hayes McDonald, Dale Pelletier, Denise Schmoyer, William R. Cannon. 587-593 [doi]
• Alignment of Multiple Proteins with an Ensemble of Hidden Markov ModelsJia Song, Chunmei Liu, Yinglei Song, Junfeng Qu. 594-599 [doi]
• Improvement of Bayesian Network Inference Using a Relaxed Gene OrderingDongxiao Zhu, Hua Li. 600-605 [doi]
• Feature Extraction from Microarray Expression Data by Integration of Semantic KnowledgeYoung-Rae Cho, Xian Xu, Woochang Hwang, Aidong Zhang. 606-611 [doi]
• Normalized Linear Transform for Cross-Platform Microarray Data IntegrationHuilin Xiong, Ya Zhang, Xue-wen Chen. 612-617 [doi]
• Logistic Ensembles for Random Spherical Linear OraclesLeif E. Peterson, Matthew Coleman. 618-623 [doi]
• Cox s Proportional Hazards Model with Lp Penalty for Biomarker Identification and Survival PredictionZhenqiu Liu. 624-628 [doi]
• Modeling Spatial-Temporal Epidemics Using STBL ModelLynne Billard, Duck-Ki Kim, Chan-Hee Lee, Sung Duck Lee, Keon-Myung Lee, Sung-Soo Kim. 629-633 [doi]