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ICMLA 2010: Washington, DC, USA
- Sorin Draghici, Taghi M. Khoshgoftaar, Vasile Palade, Witold Pedrycz, M. Arif Wani, Xingquan Zhu:
The Ninth International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, USA, 12-14 December 2010. IEEE Computer Society 2010, ISBN 978-0-7695-4300-0
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 Gamelas 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 Gamelas 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 Marzat, Hélène Piet-Lahanier:
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, Clément 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 K. 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 Alejandro Madera-Ramírez, Víctor 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 P. 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 A. 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 H. 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 Ibne 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, André 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, Ramón Galán:
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 Analysis 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 Ertüzün:
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, Özkan Ünsal:
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