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ORCIDICMLA 2013: Miami, FL, USA
- 12th International Conference on Machine Learning and Applications, ICMLA 2013, Miami, FL, USA, December 4-7, 2013, Volume 1. IEEE 2013, ISBN 978-0-7695-5144-9
Ensemble-Based Methods I
- Adrian Rosebrock, Tim Oates, Jesus J. Caban:
Ecosembles: A Rapidly Deployable Image Classification System Using Feature-Views. 1-8 - Adam Drake, Dan Ventura:
An Empirical Comparison of Spectral Learning Methods for Classification. 9-14 - Madalina Fiterau, Artur Dubrawski:
Informative Projection Recovery for Classification, Clustering and Regression. 15-20 - Carlos A. Quintero
, Fernando Lozano:
Locally Linear Minimum Spanning Trees for Manifold Learning. 21-26
Ensemble-Based Methods II
- Kehan Gao, Taghi M. Khoshgoftaar, Amri Napolitano:
Improving Software Quality Estimation by Combining Boosting and Feature Selection. 27-33 - I. Chebil, Mohamed Elati, Céline Rouveirol, G. Santini:
SetNet: Ensemble Method Techniques for Learning Regulatory Networks. 34-39 - Cailing Dong, Bin Zhou:
An Ensemble Learning Framework for Online Web Spam Detection. 40-45 - Muhammad Shaheryar, Mehrosh Khalid, Ali Mustafa Qamar:
Rot-SiLA: A Novel Ensemble Classification Approach Based on Rotation Forest and Similarity Learning Using Nearest Neighbor Algorithm. 46-51
Kernel-Based Methods
- Taher A. Dameh, Wael Abd-Almageed, Mohamed Hefeeda:
Distributed Kernel Matrix Approximation and Implementation Using Message Passing Interface. 52-57 - Richard E. Edwards, Hao Zhang, Lynne E. Parker, Joshua R. New:
Approximate l-Fold Cross-Validation with Least Squares SVM and Kernel Ridge Regression. 58-64 - Cecille Freeman, Dana Kulic, Otman Basir:
Multi-modal Tree-Based SVM Classification. 65-71 - Yinan Yu, Tomas McKelvey, Sun-Yuan Kung:
Kernel SODA: A Feature Reduction Technique Using Kernel Based Analysis. 72-78
Supervised Learning Methods I
- Nipun Batra, Haimonti Dutta, Amarjeet Singh:
INDiC: Improved Non-intrusive Load Monitoring Using Load Division and Calibration. 79-84 - Shashank Srikant, Varun Aggarwal:
Automatic Grading of Computer Programs: A Machine Learning Approach. 85-92 - Zhemin Zhu, Djoerd Hiemstra, Peter M. G. Apers, Andreas Wombacher:
Empirical Co-occurrence Rate Networks for Sequence Labeling. 93-98 - Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Daniel P. W. Ellis:
Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps. 99-104 - Gheorghe Tecuci, Mihai Boicu, Dorin Marcu, David Schum:
How Learning Enables Intelligence Analysts to Rapidly Develop Practical Cognitive Assistants. 105-110
Supervised Learning Methods II
- Nicolas Sutton-Charani, Sébastien Destercke, Thierry Denoeux:
Learning Decision Trees from Uncertain Data with an Evidential EM Approach. 111-116 - Nicolas Cheifetz, Allou Samé, Patrice Aknin, Emmanuel De Verdalle, Damien Chenu:
A Sequential Testing Procedure for Multiple Change-Point Detection in a Stream of Pneumatic Door Signatures. 117-122 - Simone Filice, Danilo Croce, Roberto Basili, Fabio Massimo Zanzotto:
Linear Online Learning over Structured Data with Distributed Tree Kernels. 123-128
Machine Learning in Bioinformatics and Computational Biology I
- Mingon Kang, Shuo Li, Dong-Chul Kim, Chunyu Liu, Baoju Zhang, Xiaoyong Wu, Jean Gao:
eQTL Mapping Study via Regularized Sparse Canonical Correlation Analysis. 129-134 - Razvan C. Bunescu, Nigel Struble, Cindy Marling, Jay Shubrook, Frank Schwartz:
Blood Glucose Level Prediction Using Physiological Models and Support Vector Regression. 135-140 - Haishan Liu, Dejing Dou, Ruoming Jin, Paea LePendu, Nigam Shah:
Mining Biomedical Ontologies and Data Using RDF Hypergraphs. 141-146 - Shuo Li, James O. Nyagilo, Digant P. Dave, Baoju Zhang, Xiaoyong Wu, Jean Gao:
A Fast Multi-component Latent Variable Regression Framework for Quantitative Analysis of Surface-Enhanced Raman Spectra. 147-152
Machine Learning in Bioinformatics and Computational Biology II
- Muhammad Farooq, Juan M. Fontana, Akua F. Boateng, Megan A. McCrory, Edward Sazonov:
A Comparative Study of Food Intake Detection Using Artificial Neural Network and Support Vector Machine. 153 - Randall Wald, Taghi M. Khoshgoftaar, David J. Dittman, Amri Napolitano:
Random Forest with 200 Selected Features: An Optimal Model for Bioinformatics Research. 154-160 - Hao Zhang, Scott C. Lenaghan, Michelle H. Connolly, Lynne E. Parker:
Zebrafish Larva Locomotor Activity Analysis Using Machine Learning Techniques. 161-166 - Juan Mantilla, Mireille Garreau, Jean-Jacques Bellanger, José Luis Paredes:
Machine Learning Techniques for LV Wall Motion Classification Based on Spatio-temporal Profiles from Cardiac Cine MRI. 167-172
Clustering
- Cody Hudson, Bernard Chen:
Variable-Length Protein Sequence Motif Extraction Using Hierarchically-Clustered Hidden Markov Models. 173-178 - Gianni Costa, Riccardo Ortale:
A Latent Semantic Approach to XML Clustering by Content and Structure Based on Non-negative Matrix Factorization. 179-184 - Jonas Degrave, Robin Van Cauwenbergh, Francis Wyffels, Tim Waegeman, Benjamin Schrauwen:
Terrain Classification for a Quadruped Robot. 185-190
Machine Learning and Applications
- Nagehan Ilhan, Sule Gündüz Ögüdücü:
Community Event Prediction in Dynamic Social Networks. 191-196 - Guang Chen, Feihu Zhang, Daniel Clarke, Alois C. Knoll:
Learning to Track Multi-target Online by Boosting and Scene Layout. 197-202 - Maxim Buzdalov, Arina Buzdalova, Anatoly Shalyto:
A First Step towards the Runtime Analysis of Evolutionary Algorithm Adjusted with Reinforcement Learning. 203-208 - Rui Guo, Hairong Qi:
Partially-Sparse Restricted Boltzmann Machine for Background Modeling and Subtraction. 209-214
Posters - Main Conference
- Arne Rost, Stephan Schadle:
The SLS-Generated Soft Robotic Hand - An Integrated Approach Using Additive Manufacturing and Reinforcement Learning. 215-220 - Xiaoming Liu, Henry O. Nyongesa, James Connan:
WMCD: A Situation Aware Multicast Congestion Detection Scheme Using Support Vector Machines in MANETs. 221-226 - William Sause:
Coordinated Reinforcement Learning Agents in a Multi-agent Virtual Environment. 227-230 - Wenya Feng, Yilin Guo, Xiaoyu Shi, Yonggan Hou:
Natural Image Segmentation Based on Precise Edge Detection. 231-234 - Fan Shi, Cheng Soon Ong, Christopher Leckie:
Applications of Class-Conditional Conformal Predictor in Multi-class Classification. 235-239 - Omar AlZoubi, Davide Fossati, Sidney K. D'Mello, Rafael A. Calvo:
Affect Detection and Classification from the Non-stationary Physiological Data. 240-245 - Juri Belikov, Sven Nomm, Eduard Petlenkov, Kristina Vassiljeva:
Application of Neural Networks Based SANARX Model for Identification and Control Liquid Level Tank System. 246-251 - Neha Gupta, Ole-Christoffer Granmo, Ashok K. Agrawala:
Arm Space Decomposition as a Strategy for Tackling Large Scale Multi-armed Bandit Problems. 252-257 - Tim Brys, Kristof Van Moffaert, Kevin Van Vaerenbergh, Ann Nowé:
On the Behaviour of Scalarization Methods for the Engagement of a Wet Clutch. 258-263 - Rosalia Maglietta, Nicola Amoroso, Stefania Bruno, Andrea Chincarini, Giovanni B. Frisoni, Paolo Inglese, Sabina Tangaro, Andrea Tateo, Roberto Bellotti:
Random Forest Classification for Hippocampal Segmentation in 3D MR Images. 264-267 - A. Fatholahzadeh:
Ordered Segment for Classification of Big Data. 268-272 - Huang Xiao, Claudia Eckert:
Indicative Support Vector Clustering with Its Application on Anomaly Detection. 273-276 - Elizabeth P. Chou, Fushing Hsieh, John Capitanio:
Computed Data-Geometry Based Supervised and Semi-supervised Learning in High Dimensional Data. 277-282 - Claudio Saccà, Michelangelo Diligenti, Marco Gori:
Collective Classification Using Semantic Based Regularization. 283-286 - Claudio Saccà, Michelangelo Diligenti, Marco Gori:
Graph and Manifold Co-regularization. 287-290 - Chathra Hendahewa, Chirag Shah:
Segmental Analysis and Evaluation of User Focused Search Process. 291-294 - Shintaro Miyamoto, Takaaki Matsumoto, Koichi Yonemoto:
Dynamic Distributed Genetic Algorithm Using Hierarchical Clustering for Flight Trajectory Optimization of Winged Rocket. 295-298 - Dave DeBarr, Hao Sun, Harry Wechsler:
Adversarial Spam Detection Using the Randomized Hough Transform-Support Vector Machine. 299-304 - Matt K. Smith, Charles C. Castello, Joshua R. New:
Machine Learning Techniques Applied to Sensor Data Correction in Building Technologies. 305-308 - Salaheddin Alakkari, John James Collins:
Eigenfaces for Face Detection: A Novel Study. 309-314 - Dingsheng Luo, Yi Wang, Xihong Wu:
Discriminative Apprenticeship Learning with Both Preference and Non-preference Behavior. 315-320 - Geeta Aggarwal, Neelima Gupta:
BEMI Bicluster Ensemble Using Mutual Information. 321-324 - Manus Ross, Corey A. Graves, John W. Campbell, Jung H. Kim:
Using Support Vector Machines to Classify Student Attentiveness for the Development of Personalized Learning Systems. 325-328 - Davi C. de L. Vieira, Paulo J. L. Adeodato, Paulo M. Goncalves Junior:
A Temporal Difference GNG-Based Algorithm That Can Learn to Control in Reinforcement Learning Environments. 329-332 - Alejandro Correa Bahnsen, Aleksandar Stojanovic, Djamila Aouada, Björn E. Ottersten:
Cost Sensitive Credit Card Fraud Detection Using Bayes Minimum Risk. 333-338 - Saeed Mehrabi, Anand Krishnan, Eric Tinsley, Jon Sligh, Natalie Crohn, Heather Bush, Jason Depasquale, Jean Bandos, Mathew Palakal:
Event Causality Identification Using Conditional Random Field in Geriatric Care Domain. 339-343 - Dong Nie, Lingzi Hong, Tingshao Zhu:
Movie Recommendation Using Unrated Data. 344-347 - Tom Johnsten, Samy Alihamad, Ashwin Kannalath, Ryan G. Benton:
Targeted Action Rule Discovery. 348-353 - Olivier Fercoq:
Parallel Coordinate Descent for the Adaboost Problem. 354-358 - Fernando Gutierrez, Dejing Dou, Adam Martini, Stephen Fickas, Hui Zong:
Hybrid Ontology-Based Information Extraction for Automated Text Grading. 359-364 - Jalal S. Alowibdi, Ugo A. Buy, Philip S. Yu:
Empirical Evaluation of Profile Characteristics for Gender Classification on Twitter. 365-369 - Bernard Chen, Roshan Doolabh, Fusheng Tang:
Determining Potential Yeast Longevity Genes via PPI Networks and Microarray Data Clustering Analysis. 370-373 - Md. Ashad Alam, Kenji Fukumizu:
Higher-Order Regularized Kernel CCA. 374-377 - Bernard Chen, Cody Hudson, Aaron Crawford, Minwoo Kim:
Protein Local Tertiary Structure Prediction Using the Adaptively-Branching FGK-DF Model. 378-381 - Maqbool Ali, Ali Mustafa Qamar, Bilal Ali:
Data Analysis, Discharge Classifications, and Predictions of Hydrological Parameters for the Management of Rawal Dam in Pakistan. 382-385 - Omar K. Shoukry, Magda B. Fayek:
Evolutionary Content Pre-fetching in Mobile Networks. 386-391 - Matteo Menna, Mario Gianni, Fiora Pirri:
Learning the Dynamic Process of Inhibition and Task Switching in Robotics Cognitive Control. 392-397 - Chirine Wolley, Mohamed Quafafou:
Scalable Expert Selection When Learning from Noisy Labelers. 398-401 - Jürgen Wiest, Felix Kunz, Ulrich Kressel, Klaus Dietmayer:
Incorporating Categorical Information for Enhanced Probabilistic Trajectory Prediction. 402-407 - Daniela Pohl, Abdelhamid Bouchachia, Hermann Hellwagner:
Online Processing of Social Media Data for Emergency Management. 408-413 - Eric V. Strobl, Shyam Visweswaran:
Deep Multiple Kernel Learning. 414-417 - Randall Wald, Taghi M. Khoshgoftaar, Ahmad Abu Shanab, Amri Napolitano:
Comparative Analysis on the Stability of Feature Selection Techniques Using Three Frameworks on Biological Datasets. 418-423 - Marian George, Nagia M. Ghanem, Mohamed A. Ismail:
Learning-Based Incremental Creation of Web Image Databases. 424-429 - Kaveh Hassani, Won-Sook Lee:
An Incremental Parallel Particle Swarm Approach for Classification Rule Discovery from Dynamic Data. 430-435 - Jose Hurtado, Napat Taweewitchakreeya, Xue Kong, Xingquan Zhu:
A Classifier Ensembling Approach for Imbalanced Social Link Prediction. 436-439 - Zhiguo Yu, Todd R. Johnson, Ramakanth Kavuluru:
Phrase Based Topic Modeling for Semantic Information Processing in Biomedicine. 440-445
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