ICMLA 2010: Washington, DC, USA

Data Acquisition, Cleansing and Categorization

• David J. Miller, Chu-Fang Lin, George Kesidis, Christopher M. Collins:
  Improved Fine-Grained Component-Conditional Class Labeling with Active Learning. 3-8
  
• Jason Van Hulse, Taghi M. Khoshgoftaar, Amri Napolitano:
  A Novel Noise Filtering Algorithm for Imbalanced Data. 9-14
  
• Shayok Chakraborty, Vineeth Nallure Balasubramanian, Sethuraman Panchanathan:
  Dynamic Batch Size Selection for Batch Mode Active Learning in Biometrics. 15-22
  
• Dan Shen, Jean-David Ruvini, Rajyashree Mukherjee, Neel Sundaresan:
  A Study of Smoothing Algorithms for Item Categorization on e-Commerce Sites. 23-28
  

Planning and Reinforcement Learning

• Yong Lin, Fillia Makedon:
  From Serve-on-Demand to Serve-on-Need: A Game Theoretic Approach. 31-36
  
• Elizabeth Duane S. Costa, Maury M. Gouvea Jr.:
  Autonomous Navigation in Dynamic Environments with Reinforcement Learning and Heuristic. 37-42
  
• Man Chon U, Zhen Li:
  Public Goods Game Simulator with Reinforcement Learning Agents. 43-49
  
• Philip R. Cook, Michael A. Goodrich:
  MMM-PHC: A Particle-Based Multi-Agent Learning Algorithm. 50-55
  

Supervised Learning

• Joaquim F. Pinto da Costa, Ricardo Sousa, Jaime S. Cardoso:
  An All-at-once Unimodal SVM Approach for Ordinal Classification. 59-64
  
• Abdullah Bawakid, Mourad Oussalah:
  Centroid-based Classification Enhanced with Wikipedia. 65-70
  
• Jaime S. Cardoso, Ricardo Sousa:
  Classification Models with Global Constraints for Ordinal Data. 71-77
  
• Qi Li, Chang-Tien Lu:
  Appearance Based Recognition Using Spatial and Discriminant Influence. 78-83
  
• Madhavi Vedula Ratnagiri, Lawrence R. Rabiner, Biing-Hwang Juang:
  Multi-Class Classification Using a New Sigmoid Loss Function for Minimum Classification Error (MCE). 84-89
  

Multi-party, Multi-modal, Multi-objective Learning

• Nesrine Elfelly, Jean-Yves Dieulot, Pierre Borne, Mohamed Benrejeb:
  A Multimodel Approach of Complex Systems Identification and Control Using Neural and Fuzzy Clustering Algorithms. 93-98
  
• Cynthia L. Johnson, Avelino J. Gonzalez:
  Learning Collaborative Behavior by Observation. 99-104
  
• Jeff Allen, John Anderson:
  Heterogeneous Imitation Learning from Demonstrators of Varying Physiology and Skill. 105-112
  
• Frank Sehnke, Alex Graves, Christian Osendorfer, Jürgen Schmidhuber:
  Multimodal Parameter-exploring Policy Gradients. 113-118
  
• Rafael Giusti, Gustavo E. A. P. A. Batista:
  Discovering Knowledge Rules with Multi-Objective Evolutionary Computing. 119-124
  

Feature Selection

• Qin Yang, Robin Gras:
  How Dependencies Affect the Capability of Several Feature Selection Approaches to Extract the Key Features. 127-134
  
• Huanjing Wang, Taghi M. Khoshgoftaar, Amri Napolitano:
  A Comparative Study of Ensemble Feature Selection Techniques for Software Defect Prediction. 135-140
  
• Sascha Klement, Thomas Martinetz:
  A New Approach to Classification with the Least Number of Features. 141-146
  
• David J. Dittman, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse:
  Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques. 147-152
  

Probabilistic and Model Based Learning

• Chen-Hsiang Yeang:
  A Probabilistic Graphical Model of Quantum Systems. 155-162
  
• Quang-Thang Dinh, Matthieu Exbrayat, Christel Vrain:
  Heuristic Method for Discriminative Structure Learning of Markov Logic Networks. 163-168
  
• Joseph Defretin, Julien Marzatz, Helene Piet-Lahanierz:
  Learning Viewpoint Planning in Active Recognition on a Small Sampling Budget: A Kriging Approach. 169-174
  
• Mohamed Nadif, Gérard Govaert:
  Model-Based Co-clustering for Continuous Data. 175-180
  

Similarity Learning for Pattern Recognition

• Ali Mustafa Qamar, Éric Gaussier:
  Similarity Learning in Nearest Neighbor and Relief Algorithm. 183-189
  
• Syed Fawad Hussain, Gilles Bisson, Clement Grimal:
  An Improved Co-Similarity Measure for Document Clustering. 190-197
  
• Ce Gao, Yixu Song, Peifa Jia:
  Multilayer Ferns: A Learning-based Approach of Patch Recognition and Homography Extraction. 198-203
  
• Qi Li, Zhonghang Xia, Guangming Xing:
  A Binocular Framework for Face Liveness Verification under Unconstrained Localization. 204-207
  
• Qi Li, Vojislav Kecman, Raied Salman:
  A Chunking Method for Euclidean Distance Matrix Calculation on Large Dataset Using Multi-GPU. 208-213
  

Kernel Learning Methods

• Richard E. Hudson, Jeremy A. Marvel, Wyatt S. Newman:
  Modeling and Training Radial Basis Functions with Integrate-and-Fire Neurons. 217-222
  
• Hideitsu Hino, Nima Reyhani, Noboru Murata:
  Multiple Kernel Learning by Conditional Entropy Minimization. 223-228
  
• Zhonghang Xia, Wenke Zhang, Manghui Tu, I-Ling Yen:
  Kernel-based Approaches for Collaborative Filtering. 229-234
  
• Vineeth Nallure Balasubramanian, Shayok Chakraborty, Sethuraman Panchanathan, Jieping Ye:
  Kernel Learning for Efficiency Maximization in the Conformal Predictions Framework. 235-242
  
• Tim vor der Brück, Hermann Helbig:
  Validating Meronymy Hypotheses with Support Vector Machines and Graph Kernels. 243-250
  

Unsupervised Learning

• Sai Venu Gopal Lolla, Lawrence L. Hoberock:
  Improved Unsupervised Clustering over Watershed-Based Clustering. 253-259
  
• Tianming Hu, Chuanren Liu, Jing Sun, Sam Yuan Sung, Peter A. Ng:
  Pairwise Constrained Clustering with Group Similarity-Based Patterns. 260-265
  
• Harry Strange, Reyer Zwiggelaar:
  Parallel Projections for Manifold Learning. 266-271
  
• Zhi Qiao, Peng Zhang, Jing He, Jinghua Yan, Li Guo:
  Learning from Multiple Related Data Streams with Asynchronous Flowing Speeds. 272-277
  

Machine Learning in Bioinformatics and Computational Biology

• Jinghua Gu, Jianhua Xuan, Yue Joseph Wang, Rebecca B. Riggins, Robert Clarke:
  Identification of Transcriptional Regulatory Networks by Learning the Marginal Function of Outlier Sum Statistic. 281-286
  
• Chen Wang, Sook S. Ha, Yue Joseph Wang, Jianhua Xuan, Eric P. Hoffman:
  Computational Analysis of Muscular Dystrophy Sub-types Using a Novel Integrative Scheme. 287-292
  
• Yajuan Wang, Carolyn Penstein Rosé, Antonio Ferreira, Dennis M. McNamara, Robert L. Kormos, James F. Antaki:
  A Classification Approach for Risk Prognosis of Patients on Mechanical Ventricular Assistance. 293-298
  
• Guangzhi Qu, Hui Wu, Ishwar Sethi, Craig T. Hartrick:
  Neuropathic Pain Scale Based Clustering for Subgroup Analysis in Pain Medicine. 299-304
  

Machine Learning and Parallel Computing

• Xavier Sierra-Canto, Francisco Madera-Ramirez, Victor Uc Cetina:
  Parallel Training of a Back-Propagation Neural Network Using CUDA. 307-312
  
• Tsung-Kai Lin, Shao-Yi Chien:
  Support Vector Machines on GPU with Sparse Matrix Format. 313-318
  
• David Pettinger, Giuseppe Di Fatta:
  Space Partitioning for Scalable K-Means. 319-324
  
• Tapio Pahikkala, Antti Airola, Tapio Salakoski:
  Speeding Up Greedy Forward Selection for Regularized Least-Squares. 325-330
  

Applications I

• Xiao-Wei Ai, Tianming Hu, Xi Li, Hui Xiong:
  Clustering High-frequency Stock Data for Trading Volatility Analysis. 333-338
  
• Ulrich Weiss, Peter Biber, Stefan Laible, Karsten Bohlmann, Andreas Zell:
  Plant Species Classification Using a 3D LIDAR Sensor and Machine Learning. 339-345
  
• Fabian Gieseke, Kai Lars Polsterer, Andreas Thom, Peter Zinn, Dominik Bomanns, Ralf-Jurgen Dettmar, Oliver Kramer, Jan Vahrenhold:
  Detecting Quasars in Large-Scale Astronomical Surveys. 352-357
  

Ensemble Learning

• Jun Li, Dacheng Tao:
  Boosted Dynamic Cognitive Activity Recognition from Brain Images. 361-366
  
• Jean Baptiste Faddoul, Boris Chidlovskii, Fabien Torre, Rémi Gilleron:
  Boosting Multi-Task Weak Learners with Applications to Textual and Social Data. 367-372
  
• Xueyi Wang, Nicholas J. Davidson:
  The Upper and Lower Bounds of the Prediction Accuracies of Ensemble Methods for Binary Classification. 373-378
  
• Amin Assareh, L. Gwenn Volkert, Joseph D. Ortiz:
  Evolutionary Selection of Regressional Predictors to Enhance the Performance of Microfossil-Based Paleotemperture Proxies. 379-385
  

Reinforcement Learning

• Omkar J. Tilak, Snehasis Mukhopadhyay:
  Decentralized and Partially Decentralized Reinforcement Learning for Distributed Combinatorial Optimization Problems. 389-394
  
• Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik:
  Multi-Agent Inverse Reinforcement Learning. 395-400
  
• Alexander Hans, Steffen Udluft:
  Ensembles of Neural Networks for Robust Reinforcement Learning. 401-406
  
• Mandana Hamidi, Amir Fijany, Jean-Guy Fontaine:
  Enhancing Inference in Relational Reinforcement Learning Via Truth Maintenance Systems. 407-413
  

Bayesian Learning

• Mark Bartlett, Iain Bate, James Cussens:
  Learning Bayesian Networks for Improved Instruction Cache Analysis. 417-423
  
• Theodoros Damoulas, Samuel Henry, Andrew Farnsworth, Michael Lanzone, Carla Gomes:
  Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel. 424-429
  
• Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Nelson F. F. Ebecken:
  Evolutionary Algorithm Using Random Multi-point Crossover Operator for Learning Bayesian Network Structures. 430-435
  
• Drausin Wulsin, Justin Blanco, Ram Mani, Brian Litt:
  Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets. 436-441
  

Online and Incremental Learning

• Kilian Förster, Samuel Monteleone, Alberto Calatroni, Daniel Roggen, Gerhard Tröster:
  Incremental kNN Classifier Exploiting Correct-Error Teacher for Activity Recognition. 445-450
  
• Christophe Rodrigues, Pierre Gérard, Céline Rouveirol, Henry Soldano:
  Incremental Learning of Relational Action Rules. 451-458
  
• Adam M. Sykulski, Niall M. Adams, Nicholas R. Jennings:
  On-Line Adaptation of Exploration in the One-Armed Bandit with Covariates Problem. 459-464
  
• Anuraag Sridhar, Arcot Sowmya, Paul Compton:
  On-line, Incremental Learning for Real-Time Vision Based Movement Recognition. 465-470
  

Machine Learning Methods for Biomedical Literature Analysis and Text Retrieval

• Neil Barrett, Jens H. Weber-Jahnke:
  Building a Biomedical Tokenizer Using the Token Lattice Design Pattern and the Adapted Viterbi Algorithm. 473-478
  
• Xiaoli Zhang, Jie Zou, Daniel X. Le, George R. Thoma:
  A Structural SVM Approach for Reference Parsing. 479-484
  
• Adrian Benton, Shawndra Hill, Lyle Ungar, Annie Chung, Charles E. Leonard, Cristin Freeman, John H. Holmes:
  A System for De-identifying Medical Message Board Text. 485-490
  
• Won Kim, W. John Wilbur:
  Improving a Gold Standard: Treating Human Relevance Judgments of MEDLINE Document Pairs. 491-498
  
• Lana Yeganova, Donald C. Comeau, W. John Wilbur:
  Identifying Abbreviation Definitions Machine Learning with Naturally Labeled Data. 499-505
  

Machine Learning in Bioinformatics and Computational Biology

• Dianwei Han, Guiliang Tang, Jun Zhang:
  A Parallel Algorithm for Predicting the Secondary Structure of Polycistronic MicroRNAs. 509-514
  
• Chunmei Liu, Hui Li, Alison Leonce, Legand L. Burge III, John Trimble, Peter Keiller, Abdul-Aziz Yakubu:
  A Heuristic Algorithm for Finding the Longest Pathways in a Biochemical Network. 515-522
  
• Faisal Rezwan, Yi Sun, Neil Davey, Rod Adams, Alistair G. Rust, Mark Robinson:
  Using Randomised Vectors in Transcription Factor Binding Site Predictions. 523-527
  
• Betty Yee Man Cheng, Jaime G. Carbonell:
  Automatic Detection of HIV Drug Resistance-Associated Mutations. 528-533
  
• Boseon Byeon, Khaled Rasheed:
  Selection of Classifier and Feature Selection Method for Microarray Data. 534-539
  
• Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi:
  Smoothing Gene Expression Using Biological Networks. 540-545
  
• Nicholas J. Davidson, Xueyi Wang:
  Non-Alignment Features Based Enzyme/Non-Enzyme Classification Using an Ensemble Method. 546-551
  

Dynamic Learning in Non-Stationary Environments

• Moamar Sayed Mouchaweh:
  Learning in Dynamic Environments: Application to the Identification of Hybrid Dynamic Systems. 555-560
  
• Lin Zhang, Hongyu Li:
  Incremental Nyström Low-Rank Decomposition for Dynamic Learning. 561-566
  
• Pierre Beauseroy, Andre Smolarz, Yuan Dong, Xiyan He:
  Dynamic Decision Method Based on Contextual Selection of Representation Subspaces. 567-572
  
• Edwin Lughofer:
  On Dynamic Selection of the Most Informative Samples in Classification Problems. 573-579
  
• Laurent Hartert, Moamar Sayed Mouchaweh:
  A Hybrid Multi-classifier to Characterize and Interpret Hemiparetic Patients Gait Coordination. 580-585
  
• Abdullah Almaksour, Éric Anquetil:
  Improving Premise Structure in Evolving Takagi-Sugeno Neuro-Fuzzy Classifiers. 586-591
  

Autonomous Machine Learning

• J. Javier Rainer, Ramon Galan:
  Learning to Be a Good Tour-Guide Robot. 595-600
  
• Malik Tahir Hassan, Asim Karim, Fahad Javed, Naveed Arshad:
  Self-Optimizing a Clustering-based Tag Recommender for Social Bookmarking Systems. 601-606
  
• Nistor Grozavu, Lazhar Labiod, Younès Bennani:
  Autonomous Clustering Characterization for Categorical Data. 607-613
  

Business Intelligent Applications and Technologies

• John C. Handley, Marie-Luise Schneider, Victor Ciriza, Jeffrey Earl:
  Extreme Volume Detection for Managed Print Services. 617-622
  
• Zhiguo Li, Gregory Kott:
  Predicting Remaining Useful Life Based on the Failure Time Data with Heavy-Tailed Behavior and User Usage Patterns Using Proportional Hazards Model. 623-628
  
• David B. Bracewell:
  Semi-Automatic WordNet Based Emotion Dictionary Construction. 629-634
  
• I-Hsien Yin, Estevam R. Hruschka Jr., Heloisa de Arruda Camargo:
  Intelligent Classification System Using a Pruned Bayes Fuzzy Rule Set. 635-640
  

Machine Learning with Multimedia Data

• Sam Davies, Denise Bland:
  Interestingness Detection in Sports Audio Broadcasts. 643-648
  
• Pedro Mercado, Hanna M. Lukashevich:
  Feature Selection in Clustering with Constraints: Application to Active Exploration of Music Collections. 649-654
  
• Erik M. Schmidt, Youngmoo E. Kim:
  Prediction of Time-Varying Musical Mood Distributions Using Kalman Filtering. 655-660
  
• Behrouz Saghafi, Deepu Rajan:
  Multi-view Clustering of Visual Words Using Canonical Correlation Analysis for Human Action Recognition. 661-666
  

Machine Learning in Energy Applications (I)

• Omer Ozkan, Muharrem Aktas, Huseyin Serdar Kuyuk, Serkan Bayraktaroglu:
  Energy Production and Economic Growth: A Causality Analaysis for Turkey Based on Computer. 669-674
  
• Faa-Jeng Lin, Jonq-Chin Hwang, Kuang-Hsiung Tan, Zong-Han Lu, Yung-Ruei Chang:
  Control of Doubly-Fed Induction Generator System Using PIDNNs. 675-680
  
• Huseyin Serdar Kuyuk, Omer Ozkan, Ramazan Kayikci, Serkan Bayraktaroglu:
  Modelling Turkey's Energy Consumption Based on Artificial Neural Network. 681-685
  
• Umut Firat, Seref Naci Engin, Murat Saraclar, Aysin Baytan Ertuzun:
  Wind Speed Forecasting Based on Second Order Blind Identification and Autoregressive Model. 686-691
  
• Ilhami Colak, Ramazan Bayindir, Orhan Kaplan, Ferhat Tas:
  DC Bus Voltage Regulation of an Active Power Filter Using a Fuzzy Logic Controller. 692-696
  

Machine Learning in Energy Applications (II)

• Ramazan Bayindir, Alper Gorgun:
  Hardware Implementation of a Real-Time Neural Network Controller Set for Reactive Power Compensation Systems. 699-703
  
• Antonietta Grasso, Jutta Willamowski, Victor Ciriza, Yves Hoppenot:
  The Personal Assessment Tool: A System Providing Environmental Feedback to Users of Shared Printers for Providing Environmental Feedback. 704-709
  
• Halil-Ibrahim Bulbul, Ozkan Unsal:
  Determination of Vocational Fields with Machine Learning Algorithm. 710-713
  
• Ilhami Colak, Seref Sagiroglu, Mehmet Demirtas, Hamdi Tolga Kahraman:
  Determining Suitability of Locations for Installation of Solar Power Station Based on Probabilistic Inference. 714-719
  
• Fujio Kurokawa, Hidenori Maruta, Jun'ya Sakemi, Akihiro Nakamura, Hiroyuki Osuga:
  A New Prediction Based Digital Control DC-DC Converter. 720-725
  
• Tina Yu:
  Modeling Occupancy Behavior for Energy Efficiency and Occupants Comfort Management in Intelligent Buildings. 726-731
  

Machine Learning Methods in Cancer and Radiation Therapy

• Jung Hun Oh, Jeffrey Craft, Rawan Al-Lozi, Manushka Vaidya, Yifan Meng, Joseph O. Deasy, Jeffrey D. Bradley, Issam El-Naqa:
  Predicting Local Failure in Lung Cancer Using Bayesian Networks. 735-739
  
• Florian Buettner, Sarah Gulliford, Steve Webb, Mike Partridge, Aisha B. Miah, Kevin J. Harrington, Christopher M. Nutting:
  Using a Bayesian Feature-selection Algorithm to Identify Dose-response Models Based on the Shape of the 3D Dose-distribution: An Example from a Head-and-neck Cancer Trial. 740-745
  
• Mark Bangert, Philipp Hennig, Uwe Oelfke:
  Using an Infinite Von Mises-Fisher Mixture Model to Cluster Treatment Beam Directions in External Radiation Therapy. 746-751
  
• Melanie Mitchell, James A. Tanyi, Arthur Y. Hung:
  Automatic Segmentation of the Prostate Using a Genetic Algorithm for Prostate Cancer Treatment Planning. 752-757
  
• Sheng You, Esra Ataer Cansizoglu, Deniz Erdogmus, James Tanyi, Jayashree Kalpathy-Cramer:
  A Novel Application of Principal Surfaces to Segmentation in 4D-CT for Radiation Treatment Planning. 758-763
  

Poster Session

• Sung Duck Lee, Duck-Ki Kim:
  Bayesian Inferences and Forecasting in Spatial Time Series Models. 767-770
  
• Shobeir Fakhraei, Hamid Soltanian-Zadeh, Farshad Fotouhi, Kost V. Elisevich:
  Consensus Feature Ranking in Datasets with Missing Values. 771-775
  
• Santhosh Pathical, Gürsel Serpen:
  Hybridization of Base Classifiers of Random Subsample Ensembles for Enhanced Performance in High Dimensional Feature Spaces. 776-781
  
• Haimonti Dutta, David L. Waltz, Karthik M. Ramasamy, Philip Gross, Ansaf Salleb-Aouissi, Hatim Diab, Manoj Pooleery, Catherine A. Schevon, Ronald Emerson:
  Patient-Specific Seizure Detection from Intra-cranial EEG Using High Dimensional Clustering. 782-787
  
• Valentina Bayer Zubek, Faisal M. Khan:
  Aggregating Multiple Biological Measurements Per Patient. 788-792
  
• Rafael Augusto Ferreira do Carmo, Fabricio Gomes de Freitas, Jerffeson Teixeira de Souza:
  Empowering Simultaneous Feature and Instance Selection in Classification Problems through the Adaptation of Two Selection Algorithms. 793-796
  
• Madhavi Vedula Ratnagiri, Lawrence R. Rabiner, Biing-Hwang Juang:
  Feature Transformation and Model Design Using Minimum Classification Error. 797-802
  
• Man Chon U, Vasim Mahamuda, Khaled Rasheed:
  On the Scalability of Supervised Learners in Metagenomics. 803-807
  
• Sai Venu Gopal Lolla, Lawrence L. Hoberock:
  On Estimation of Quantiles for Pairwise Distances. 808-812
  
• Yarin Gal, Mireille Avigal:
  Overcoming Alpha-Beta Limitations Using Evolved Artificial Neural Networks. 813-818
  
• Mónica Millán-Giraldo, Javier Salvador Sánchez, V. Javier Traver:
  A Comparison of Techniques for Handling Incomplete Input Data with a Focus on Attribute Relevance Influence. 819-822
  
• Malak Alshawabkeh, Micha Moffie, Fatemeh Azmandian, Javed A. Aslam, Jennifer G. Dy, David R. Kaeli:
  Effective Virtual Machine Monitor Intrusion Detection Using Feature Selection on Highly Imbalanced Data. 823-827
  
• Thashmee Karunaratne, Henrik Boström, Ulf Norinder:
  Pre-Processing Structured Data for Standard Machine Learning Algorithms by Supervised Graph Propositionalization - A Case Study with Medicinal Chemistry Datasets. 828-833
  
• Nobuyuki Ohmori, Tatsunori Mori:
  Novel Approach for Test Methods Automatic Selection in Product Reliability: Improved Method for Acquiring Part-Whole Relation. 834-839
  
• Sebastian Bohlmann, Volkhard Klinger, Helena Szczerbicka:
  System Identification with Multi-Agent-based Evolutionary Computation Using a Local Optimization Kernel. 840-845
  
• Panganai Gomo, Mike Spann:
  Power Iteration Denoising. 846-850
  
• Bartlomiej Sniezynski, Wojciech Wójcik, Jan D. Gehrke, Janusz Wojtusiak:
  Combining Rule Induction and Reinforcement Learning: An Agent-based Vehicle Routing. 851-856
  
• Diego Uribe:
  Domain Adaptation in Sentiment Classification. 857-860
  
• Jian Zhang:
  The Influence Machine: Nonnegative Instance-Space Learning with Differentiated Regularization. 861-866
  
• Alexander M. Duda, Stephen E. Levinson:
  Nonlinear Dynamical Multi-Scale Model of Associative Memory. 867-872
  
• Hanene Azzag, Mustapha Lebbah, Aymen Arfaoui:
  Map-TreeMaps: A New Approach for Hierarchical and Topological Clustering. 873-878
  
• Alina Lazar:
  A Comparison of Linear Support Vector Machine Algorithms on Large Non-Sparse Datasets. 879-882
  
• Thomas P. Karnowski, Itamar Arel, Derek Rose:
  Deep Spatiotemporal Feature Learning with Application to Image Classification. 883-888
  
• Gonzalo A. Ruz, Eric Goles Ch.:
  Learning Gene Regulatory Networks with Predefined Attractors for Sequential Updating Schemes Using Simulated Annealing. 889-894
  
• V. Suresh Kumar, S. Vijaya Chandra, C. Susil Kumar:
  Neuro-Fuzzy Function Approximations Using Feedforward Networks - An Application of Sigmoidal Signal. 895-898
  
• Jan Outrata:
  Boolean Factor Analysis for Data Preprocessing in Machine Learning. 899-902
  
• Gustavo E. A. P. A. Batista, Bilson J. L. Campana, Eamonn J. Keogh:
  Classification of Live Moths Combining Texture, Color and Shape Primitives. 903-906
  
• Pedro Canotilho Ribeiro, Plinio Moreno, José Santos-Victor:
  Unsupervised and Online Update of Boosted Temporal Models: The UAL2Boost. 907-912
  
• Soumi Ray, Tim Oates:
  Discovering and Characterizing Hidden Variables in Streaming Multivariate Time Series. 913-916
  
• Akshay Vashist, Siun-Chuon Mau, Alexander Poylisher, Ritu Chadha, Abhrajit Ghosh:
  Predicting End-to-end Network Load. 917-920
  
• Omar Arif, Patricio A. Vela, Wayne Daley:
  Pre-image Problem in Manifold Learning and Dimensional Reduction Methods. 921-924
  
• Abid M. Malik:
  Spatial Based Feature Generation for Machine Learning Based Optimization Compilation. 925-930
  
• Sohan Seth, Jose C. Principe:
  Variable Selection: A Statistical Dependence Perspective. 931-936
  
• Juan Luo, Alexander Brodsky:
  An Optimal Regression Algorithm for Piecewise Functions Expressed as Object-Oriented Programs. 937-942
  
• Jervis Pinto, Alan Fern, Tim Bauer, Martin Erwig:
  Robust Learning for Adaptive Programs by Leveraging Program Structure. 943-948
  
• Man Chon U, Khaled Rasheed:
  A Relative Tendency Based Stock Market Prediction System. 949-953
  
• Wei Peng:
  Constrained Nonnegative Tensor Factorization for Clustering. 954-957
  
• Foaad Khosmood, Robert Levinson:
  Automatic Synonym and Phrase Replacement Show Promise for Style Transformation. 958-961
  

Posters from Special Sessions

• Antonio Jimeno-Yepes, Alan R. Aronson:
  Query Expansion for UMLS Metathesaurus Disambiguation Based on Automatic Corpus Extraction. 965-968
  
• Dazhuo Li, Fahim Mohammad, Eric C. Rouchka:
  A Bayesian Nonparametric Model for Joint Relation Integration and Domain Clustering. 969-974
  
• Sonjia Waxmonsky, John Goldsmith, Andrey Rzhetsky:
  Discovering and Counting Biomedical Verbs. 975-978
  
• Hui Li, Chunmei Liu, Xumin Liu, Macire Diakite, Legand L. Burge III, Abdul-Aziz Yakubu, William M. Southerland:
  Peptide Sequence Tag-Based Blind Identification-based SVM Model. 979-984
  
• J. Kildea, M. Evans, W. Parker:
  A Framework for Comprehensive Electronic QA in Radiation Therapy. 985-988
  
• Antti Airola, Tapio Pahikkala, Jorma Boberg, Tapio Salakoski:
  Applying Permutation Tests for Assessing the Statistical Significance of Wrapper Based Feature Selection. 989-994
  
• Rezarta Islamaj Dogan, Aurélie Névéol, Zhiyong Lu:
  A Textual Representation Scheme for Identifying Clinical Relationships in Patient Records. 995-998
  
• Liu Dan, Yue KaiDuan:
  The Design and Application of the Public Booking Service System. 999-1002
  

ICMLA Challenge Posters

• Theodoros Giannakopoulos, Sergios Petridis:
  Unsupervised Speaker Clustering in a Linear Discriminant Subspace. 1005-1009
  
• Ondej Sykora:
  Speaker Clustering Using Trails in Feature Space. 1010-1014
  
• Jianfei Wu, Loai Al Nimer, Omar Al Azzam, Charith Chitraranjan, Saeed Salem, Anne M. Denton:
  Sequential Data Clustering. 1015-1020
  

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