ICMLA 2008: San Diego, California, USA

Bayesian Learning

• Silvia Chiappa:
  A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation. 3-9
  
• Ken Ueno, Toshio Hayashi, Koichiro Iwata, Nobuyoshi Honda, Youichi Kitahara, Topon Kumar Paul:
  Prioritizing Health Promotion Plans with k-Bayesian Network Classifier. 10-15
  
• Lifeng Shang, Kwok-Ping Chan:
  Temporal Exemplar-Based Bayesian Networks for Facial Expression Recognition. 16-22
  
• Ole-Christoffer Granmo:
  A Bayesian Learning Automaton for Solving Two-Armed Bernoulli Bandit Problems. 23-30
  

Support Vector Machines

• Ángela Blanco, Manuel Martín-Merino, Javier De Las Rivas:
  Combining Dissimilarities in a Hyper Reproducing Kernel Hilbert Space for Complex Human Cancer Prediction. 33-39
  
• André Stuhlsatz, Hans-Günter Meier, Andreas Wendemuth:
  Making the Lipschitz Classifier Practical via Semi-infinite Programming. 40-47
  
• Nisrine Jrad, Edith Grall-Maës, Pierre Beauseroy:
  A Supervised Decision Rule for Multiclass Problems Minimizing a Loss Function. 48-53
  
• Catarina Silva, Bernardete Ribeiro:
  Selecting Examples in Manifold Reduced Feature Space for Active Learning. 54-59
  
• Li Chen, Jianhua Xuan, Yue Joseph Wang, Rebecca B. Riggins, Robert Clarke:
  Network-Constrained Support Vector Machine for Classification. 60-65
  
• Jared Dinerstein, Sabra Dinerstein, Parris K. Egbert, Stephen W. Clyde:
  Learning-Based Fusion for Data Deduplication. 66-71
  

Reinforcement Learning and Markov Processes

• Sertan Girgin, Philippe Preux:
  Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture. 75-82
  
• Abdeslam Boularias:
  A Predictive Model for Imitation Learning in Partially Observable Environments. 83-90
  
• Ioannis Rexakis, Michail G. Lagoudakis:
  Classifier-Based Policy Representation. 91-98
  
• Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chaib-draa:
  Prediction-Directed Compression of POMDPs. 99-105
  
• K. Nunez, Jianhua Chen, Peter P. Chen, Guoli Ding, Robert F. Lax, Brian D. Marx:
  Empirical Comparison of Greedy Strategies for Learning Markov Networks of Treewidth k. 106-111
  

Ensemble-Based Methods

• Sherif Abdelazeem:
  A Greedy Approach for Building Classification Cascades. 115-120
  
• Henrik Boström:
  Calibrating Random Forests. 121-126
  
• Tuve Löfström, Ulf Johansson, Henrik Boström:
  On the Use of Accuracy and Diversity Measures for Evaluating and Selecting Ensembles of Classifiers. 127-132
  

Inductive Learning

• Jun Won Lee, Christophe G. Giraud-Carrier:
  New Insights into Learning Algorithms and Datasets. 135-140
  
• Petr Hoffmann:
  Learning Analysis by Reduction from Positive Data Using Reverible Languages. 141-146
  
• Boseon Byeon, Khaled Rasheed:
  Simultaneously Removing Noise and Selecting Relevant Features for High Dimensional Noisy Data. 147-152
  
• Andres Folleco, Taghi M. Khoshgoftaar, Amri Napolitano:
  Comparison of Four Performance Metrics for Evaluating Sampling Techniques for Low Quality Class-Imbalanced Data. 153-158
  

Statistical Learning

• Dwi Sianto Mansjur, Biing-Hwang Juang:
  Improving Kernel Density Classifier Using Corrective Bandwidth Learning with Smooth Error Loss Function. 161-167
  
• Qiang Fu, Biing-Hwang Juang:
  An Investigation of Non-Uniform Error Cost Function Design in Automatic Speech Recognition. 168-173
  
• Bo Liu, Hongbin Zhang, WenAn Chen:
  Boundary Constrained Manifold Unfolding. 174-181
  
• Johannes Mohr, Sambu Seo, Imke Puls, Andreas Heinz, Klaus Obermayer:
  Target Selection: A New Learning Paradigm and Its Application to Genetic Association Studies. 182-187
  
• Karim T. Abou-Moustafa, Frank P. Ferrie:
  Regularized Minimum Volume Ellipsoid Metric for Query-Based Learning. 188-193
  
• Sophia Sakellaridi, Haw-ren Fang, Yousef Saad:
  Graph-Based Multilevel Dimensionality Reduction with Applications to Eigenfaces and Latent Semantic Indexing. 194-200
  

Unsupervised Methods

• Rami N. Mahdi, Eric C. Rouchka:
  Model Based Unsupervised Learning Guided by Abundant Background Samples. 203-210
  
• Gilles Bisson, Syed Fawad Hussain:
  Chi-Sim: A New Similarity Measure for the Co-clustering Task. 211-217
  
• Mustapha Lebbah, Younès Bennani, Hamid Benhadda:
  Relational Analysis for Consensus Clustering from Multiple Partitions. 218-223
  
• Nicoleta Rogovschi, Mustapha Lebbah, Younès Bennani:
  Probabilistic Mixed Topological Map for Categorical and Continuous Data. 224-231
  
• Haw-ren Fang, Yousef Saad:
  Farthest Centroids Divisive Clustering. 232-238
  
• Lucian Alecu, Hervé Frezza-Buet:
  Are Neural Fields Suitable for Vector Quantization? 239-244
  

Image Processing

• Lei Ding, Alper Yilmaz:
  Image Segmentation as Learning on Hypergraphs. 247-252
  
• Sungmoon Jeong, Sang-Woo Ban, Minho Lee:
  Autonomous Detector Using Saliency Map Model and Modified Mean-Shift Tracking for a Blind Spot Monitor in a Car. 253-258
  
• Volker Willert, Julian Eggert, Marc Toussaint, Edgar Körner:
  Probabilistic Exploitation of the Lucas and Kanade Smoothness Constraint. 259-266
  
• C. Krishna Mohan, N. Dhananjaya, B. Yegnanarayana:
  Video Shot Segmentation Using Late Fusion Technique. 267-270
  
• Wooyoung Kim, James M. Rehg:
  Detection of Unnatural Movement Using Epitomic Analysis. 271-276
  

Evolutionary Algorithms and Genetic Programming

• Manoel Fernando Alonso Gadi, Xidi Wang, Alair Pereira do Lago:
  Comparison with Parametric Optimization in Credit Card Fraud Detection. 279-285
  
• Matej Sprogar:
  A Study of GP's Division Operators for Symbolic Regression. 286-291
  
• Fatemeh Vafaee, Weimin Xiao, Peter C. Nelson, Chi Zhou:
  Adaptively Evolving Probabilities of Genetic Operators. 292-299
  
• Melissa Danforth:
  Scalable Patch Management Using Evolutionary Analysis of Attack Graphs. 300-307
  

Applications

• Hang T. Nguyen, Ian T. Nabney:
  Combining the Wavelet Transform and Forecasting Models to Predict Gas Forward Prices. 311-317
  
• Caio Soares, Christin Hamilton, Lacey Montgomery, Juan E. Gilbert:
  Improving Accuracy in the Montgomery County Corrections Program Using Case-Based Reasoning. 318-323
  
• Martin Schierle, Daniel Trabold:
  Extraction of Failure Graphs from Structured and Unstructured Data. 324-330
  
• Zhuo Sun, Yiqiang Chen, Juan Qi, Junfa Liu:
  Adaptive Localization through Transfer Learning in Indoor Wi-Fi Environment. 331-336
  
• John Lees-Miller, Fraser Anderson, Bret Hoehn, Russell Greiner:
  Does Wikipedia Information Help Netflix Predictions? 337-343
  
• Cristina Picus, Luigi Cambrini, Wolfgang Herzner:
  Boltzmann Machine Topology Learning for Distributed Sensor Networks Using Loopy Belief Propagation Inference. 344-349
  
• Haimonti Dutta, Ananda Matthur:
  Distributed Optimization Strategies for Mining on Peer-to-Peer Networks. 350-355
  
• Erdal Kayacan, Yesim Oniz, Okyay Kaynak, Andon V. Topalov:
  Adaptive Control of Antilock Braking System Using Grey Multilayer Feedforward Neural Networks. 356-361
  
• Leonardo Rigutini, Michelangelo Diligenti, Marco Maggini, Marco Gori:
  A Fully Automatic Crossword Generator. 362-367
  
• Alexander Brodsky, Juan Luo, Hadon Nash:
  CoReJava: Learning Functions Expressed as Object-Oriented Programs. 368-375
  
• Jun Nishimura, Nobuo Sato, Tadahiro Kuroda:
  Speaker Siglet Detection for Business Microscope. 376-381
  
• Daniela Mayumi Ushizima, Oliver Rübel, Prabhat, Gunther H. Weber, E. Wes Bethel, Cecilia R. Aragon, Cameron G. R. Geddes, Estelle Cormier-Michel, Bernd Hamann, Peter Messmer, Hans Hagen:
  Automated Analysis for Detecting Beams in Laser Wakefield Simulations. 382-387
  
• Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinberger, Lawrence K. Saul:
  Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data. 388-395
  
• Andriy Burkov, Brahim Chaib-draa:
  Distributed Planning in Stochastic Games with Communication. 396-401
  
• Victor Eijkhout, Erika Fuentes:
  Multi-stage Learning of Linear Algebra Algorithms. 402-407
  
• Mir Shahriar Emami:
  Optimization on a Novel Quantum Greedy Approach Based on Learning Strategy for Zero and One Knapsack Problem and Evaluation. 408-414
  
• Etienne Côme, Zohra Leila Cherfi, Latifa Oukhellou, Patrice Aknin:
  Semi-supervised IFA with Prior Knowledge on the Mixing Process: An Application to a Railway Device Diagnosis. 415-420
  
• John Byrnes:
  Estimation of Gaussian Mixtures from Moments. 421-425
  
• Dragana Veljkovic, Kay A. Robbins:
  Force Feature Spaces for Visualization and Classification. 426-433
  

From Biological Intelligence to Machine Intelligence: Algorithm Abstraction, Evaluation, and Validation

• Thomas Lochmatter, Alcherio Martinoli:
  Simulation Experiments with Bio-inspired Algorithms for Odor Source Localization in Laminar Wind Flow. 437-443
  
• W. Li, J. Sutton, Y. Li:
  Integration of Chemical and Visual Sensors for Identifying an Odor Source in Near Shore Ocean Conditions. 444-449
  
• Sang C. Suh, Sam Saffer, Naveen Kumar Adla:
  Extraction of Meaningful Rules in a Medical Database. 450-456
  
• Bobbie-Jo M. Webb-Robertson, Melissa M. Matzke, Christopher S. Oehmen:
  Dimension Reduction via Unsupervised Learning Yields Significant Computational Improvements for Support Vector Machine Based Protein Family Classification. 457-462
  
• Matthew D. Eyster, Michael J. Mendenhall, Steven K. Rogers:
  A Qualia Framework for Ladar 3D Object Classification. 463-469
  
• J. Sutton, W. Li:
  Development of CPT_M3D for Multiple Chemical Plume Tracing and Source Identification. 470-475
  
• Atsushi Kohnotoh, Hiroshi Ishida:
  Active Stereo Olfactory Sensing System for Localization of Gas/Odor Source. 476-481
  
• Mari Ohashi, Yuichi Minagawa, Yuki Myoren, Hiroshi Ishida:
  Crayfish Robot Employing Flow Induced by Waving to Locate a Chemical Source. 482-488
  
• Pedro Angelo Morais de Sousa, Lino Marques, Anibal T. de Almeida:
  Toward Chemical-Trail Following Robots. 489-494
  

Applications of Machine Learning in Medicine and Biology

• Philip Igwe, Mahdieh Emrani, Samer Adeeb, Doug Hill:
  Assessing Torso Deformity in Scoliosis Using Self-Organizing Neural Networks (SNN). 497-502
  
• Johannes Mohr, Sambu Seo, Klaus Obermayer:
  Automated Microarray Classification Based on P-SVM Gene Selection. 503-507
  
• Caio Soares, Lacey Montgomery, Kenneth Rouse, Juan E. Gilbert:
  Automating Microarray Classification Using General Regression Neural Networks. 508-513
  
• M. Arif Wani:
  Incremental Hybrid Approach for Microarray Classification. 514-520
  

Machine Learning Applications in Radiotherapy

• Kenji Suzuki:
  Segmentation of Lesions with Improved Specificity in Computer-Aided Diagnosis Using a Massive-Training Artificial Neural Network (MTANN). 523-527
  
• Martin J. Murphy:
  Using Neural Networks to Predict Breathing Motion. 528-532
  
• Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconcelos, Steve B. Jiang:
  Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques. 533-538
  
• Issam El-Naqa, Jeffrey D. Bradley, Joseph Deasy:
  Nonlinear Kernel-Based Approaches for Predicting Normal Tissue Toxicities. 539-544
  
• Shiva K. Das, Shifeng Chen, Joseph O. Deasy, Sumin Zhou, Fang-Fang Yin, Lawrence B. Marks:
  Decision Fusion of Machine Learning Models to Predict Radiotherapy-Induced Lung Pneumonitis. 545-550
  
• Xiaoli Tang, Tong Lin, Steve B. Jiang:
  Towards On-line Treatment Verification Using cine EPID for Hypofractionated Lung Radiotherapy. 551-555
  

Machine Learning and Data Mining Methods in Bioinformatics

• Cecilia Sönströd, Ulf Johansson, Ulf Norinder, Henrik Boström:
  Comprehensible Models for Predicting Molecular Interaction with Heart-Regulating Genes. 559-564
  
• Scott F. Smith:
  RNA Search Acceleration with Genetic Algorithm Generated Decision Trees. 565-570
  
• Cécile Low-Kam, Anne Laurent, Maguelonne Teisseire:
  Detection of Sequential Outliers Using a Variable Length Markov Model. 571-576
  
• Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell:
  Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. 577-582
  
• Donald Geman, Bahman Afsari, Aik Choon Tan, Daniel Q. Naiman:
  Microarray Classification from Several Two-Gene Expression Comparisons. 583-585
  

Statistical Data Mining and Machine Learning in Cancer Epidemiology and Cancer

• Dechang Chen, Kai Xing, Donald Henson, Li Sheng:
  Group Testing in the Development of an Expanded Cancer Staging System. 589-594
  
• Jia Song, Chunmei Liu, Yinglei Song, Junfeng Qu:
  Clustering for DNA Microarray Data Analysis with a Graph Cut Based Algorithm. 595-598
  
• Zhenqiu Liu:
  Detecting Disease Associated Genes and Gene-Gene Interactions with Penalized AUC Maximization. 599-603
  

Application of Machine Learning in Constructing Biopatterns and Analyzing Bioprofiles

• Azzam F. Taktak, Antonio Eleuteri, M. S. Hane Aung, Paulo J. G. Lisboa, Laurence Desjardins, Bertil E. Damato:
  External Validation of a Bayesian Neural Network Model in Survival Analysis. 607-612
  
• Paulo J. G. Lisboa, Enrique Romero, Alfredo Vellido, Margarida Julià-Sapé, Carles Arús:
  Classification, Dimensionality Reduction, and Maximally Discriminatory Visualization of a Multicentre 1H-MRS Database of Brain Tumors. 613-618
  
• Daniele Soria, Jonathan M. Garibaldi, Elia Biganzoli, Ian O. Ellis:
  A Comparison of Three Different Methods for Classification of Breast Cancer Data. 619-624
  
• Ioannis N. Dimou, Michalis E. Zervakis:
  Support Vector Machines versus Decision Templates in Biomedical Decision Fusion. 625-630
  
• Qingzhong Liu, Mengyu Qiao, Andrew H. Sung:
  Distance Metric Learning and Support Vector Machines for Classification of Mass Spectrometry Proteomics Data. 631-636
  
• Leif E. Peterson, Kirill V. Larin:
  Hermite/Laguerre Neural Networks for Classification of Artificial Fingerprints from Optical Coherence Tomography. 637-643
  
• Ana S. Fernandes, Ian H. Jarman, Terence A. Etchells, José Manuel Fonseca, Elia Biganzoli, Chris Bajdik, Paulo J. G. Lisboa:
  Missing Data Imputation in Longitudinal Cohort Studies: Application of PLANN-ARD in Breast Cancer Survival. 644-649
  
• Federico Ambrogi, Elena Raimondi, Daniele Soria, Patrizia Boracchi, Elia Biganzoli:
  Cancer Profiles by Affinity Propagation. 650-655
  

Machine Learning in Information and System Security Issues

• Yuchun Tang, Yuanchen He, Sven Krasser:
  Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection. 659-664
  
• Karim Tabia, Salem Benferhat:
  On the Use of Decision Trees as Behavioral Approaches in Intrusion Detection. 665-670
  
• Qingzhong Liu, Andrew H. Sung, Mengyu Qiao:
  Video Steganalysis Based on the Expanded Markov and Joint Distribution on the Transform Domains Detecting MSU StegoVideo. 671-674
  

Machine Learning Applications

• Lan Huang, Chunguang Zhou, Yu-qin Zhou, Zhe Wang:
  Research on Data Mining Algorithms for Automotive Customers' Behavior Prediction Problem. 677-681
  
• Chingwei Chang, Kwoting Fang, Chiungyu Huang:
  Dynamic Knowledge Management Procedure Using Fuzzy Clustering. 682-687
  
• Cyril Laurier, Jens Grivolla, Perfecto Herrera:
  Multimodal Music Mood Classification Using Audio and Lyrics. 688-693
  
• Ilhami Colak, Seref Sagiroglu, Hamdi Tolga Kahraman:
  A User Modeling Approach to Web Based Adaptive Educational Hypermedia Systems. 694-699
  

Workshop: Machine Learning in Biomedicine and Bioinformatics

• Peng Chen, Chunmei Liu, Legand L. Burge III, Mahmood Mohammad, William M. Southerland, Clay Gloster:
  Prediction of Inter-residue Contact Clusters from Hydrophobic Cores. 703-708
  
• Yue Fan, Mark A. Kon, Charles DeLisi:
  Ensemble Machine Methods for DNA Binding. 709-716
  
• Xiaotong Lin, Xue-wen Chen:
  Gene Network Learning Using Regulated Dynamic Bayesian Network Methods. 717-722
  
• Dechang Chen, Kai Xing, Donald Henson, Li Sheng, Arnold M. Schwartz, Xiuzhen Cheng:
  A Clustering Approach in Developing Prognostic Systems of Cancer Patients. 723-728
  
• Sang-Chul Lee, William McFadden, Peter Bajcsy:
  Text, Image and Vector Graphics Based Appraisal of Contemporary Documents. 729-734
  

Posters

• Shyue-Liang Wang, Ting-Zheng Lai, Tzung-Pei Hong, Yu-Lung Wu:
  Efficient Hiding of Collaborative Recommendation Association Rules with Updates. 737-740
  
• Thanh Minh Nguyen, Q. M. Jonathan Wu:
  A Combination of Positive and Negative Fuzzy Rules for Image Classification Problem. 741-746
  
• Seiichi Ozawa, Asim Roy:
  Incremental Learning for Multitask Pattern Recognition Problems. 747-751
  
• Jaisheel Mistry, Fulufhelo Vincent Nelwamondo, Tshilidzi Marwala:
  Estimating Missing Data and Determining the Confidence of the Estimate Data. 752-755
  
• Mary M. Randolph-Gips:
  A New Neural Network to Process Missing Data without Imputation. 756-762
  
• Teresa Gonçalves, Paulo Quaresma:
  Text Classification Using Tree Kernels and Linguistic Information. 763-768
  
• Weiya Shi, Yue-Fei Guo, Cheng Jin, Xiangyang Xue:
  An Improved Generalized Discriminant Analysis for Large-Scale Data Set. 769-772
  
• Congle Zhang, Dikan Xing:
  Knowledge-Supervised Learning by Co-clustering Based Approach. 773-776
  
• Mehrdad Fatourechi, Rabab K. Ward, Steven G. Mason, Jane Huggins, Alois Schlögl, Gary E. Birch:
  Comparison of Evaluation Metrics in Classification Applications with Imbalanced Datasets. 777-782
  
• Cesar Koirala, Khaled Rasheed:
  Comparison of the Effects of Morphological and Ontological Information on Text Categorization. 783-786
  
• Ayse Cufoglu, Mahi Lohi, Kambiz Madani:
  A Comparative Study of Selected Classification Accuracy in User Profiling. 787-791
  
• Claudio A. Policastro, Gabriel D. Pais, Vitor R. Munhoz, Roseli A. F. Romero, Giovana Zuliani, Ednaldo Brigante Pizzolato:
  Applying Learning by Tutelage and Multimodal Interface to Sociable Robots. 792-795
  
• Eija Haapalainen, Perttu Laurinen, Juha Röning, Hannu Kinnunen:
  Estimation of Exercise Energy Expenditure Using a Wrist-Worn Accelerometer: A Linear Mixed Model Approach with Fixed-Effect Variable Selection. 796-801
  
• Pekka Siirtola, Perttu Laurinen, Juha Röning:
  A Weighted Distance Measure for Calculating the Similarity of Sparsely Distributed Trajectories. 802-807
  
• Jun Won Lee, Christophe G. Giraud-Carrier:
  Predicting Algorithm Accuracy with a Small Set of Effective Meta-Features. 808-812
  
• Erik Linstead, Cristina Videira Lopes, Pierre Baldi:
  An Application of Latent Dirichlet Allocation to Analyzing Software Evolution. 813-818
  
• Robson Eisinger, Roseli A. F. Romero, Rudinei Goularte:
  Machine Learning Techniques Applied to Dynamic Video Adapting. 819-822
  
• Marcin J. Mizianty, Lukasz A. Kurgan, Marek R. Ogiela:
  Comparative Analysis of the Impact of Discretization on the Classification with Naïve Bayes and Semi-Naïve Bayes Classifiers. 823-828
  
• Alberione Braz da Silva, João Luís Garcia Rosa:
  Biological Plausibility in Artificial Neural Networks: An Improvement on Earlier Models. 829-834
  
• Na Luo, Fuyu Yuan, Wanli Zuo, Fengling He:
  Research of PU Text Semi-supervised Classification Based on Ontology Feature Extraction. 835-838
  
• Nhien-An Le-Khac, Lamine M. Aouad, M. Tahar Kechadi:
  Handling Large Volumes of Mined Knowledge with a Self-Reconfigurable Topology on Distributed Systems. 839-842
  
• Derrick Takeshi Mirikitani, Nikolay I. Nikolaev:
  Dynamic Modeling with Ensemble Kalman Filter Trained Recurrent Neural Networks. 843-848
  
• Chi-Chang Chang:
  Entropy-Based Defuzzification Method with Expert's Epistemic Uncertainty for Deteriorating Repairable Systems. 849-852
  
• Iren Valova, Daniel MacLean, Derek Beaton:
  Identification of Patterns via Region-Growing Parallel SOM Neural Network. 853-858
  
• Ling Cen, Wee Ser, Zhu Liang Yu:
  Speech Emotion Recognition Using Canonical Correlation Analysis and Probabilistic Neural Network. 859-862
  
• Zhonghang Xia, Houduo Qi, Manghui Tu, Wenke Zhang:
  Data Integration for Recommendation Systems. 863-866
  
• Sara Izadi, Ching Y. Suen:
  Online Writer-Independent Character Recognition Using a Novel Relational Context Representation. 867-870
  
• Hitoshi Yamasaki, Takayoshi Shoudai:
  Mining of Frequent Externally Extensible Outerplanar Graph Patterns. 871-876
  
• Tich Phuoc Tran, Pohsiang Tsai, Tony Jan:
  A Multi-expert Classification Framework with Transferable Voting for Intrusion Detection. 877-882
  
• Hairong Lei, Joe Michael Kniss:
  Protein-Protein Interaction Prediction Using Single Class SVM. 883-887
  
• Claudio Cifarelli, G. Manfredi, L. Nieddu:
  Statistical Face Recognition via a k-Means Iterative Algorithm. 888-891
  
• Chidentree Treesatayapun, Vicente Parra-Vega, Francisco José Ruiz Sanchez:
  Nonlinear Discrete-Time Adaptive Controller Based on Fuzzy Rules Emulated Network and Its Estimated Gradient. 892-895
  
• Lin Guan, Tong-wen Wang, Yao Zhang, Li-jun Zhang:
  A Data Driven Knowledge Acquisition Method and Its Application in Power System Dynamic Stability Assessment. 896-899
  
• Michael Gashler, Christophe G. Giraud-Carrier, Tony R. Martinez:
  Decision Tree Ensemble: Small Heterogeneous Is Better Than Large Homogeneous. 900-905
  

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