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ICMLA 2005: Los Angeles, California, USA
- M. Arif Wani, Mariofanna G. Milanova, Lukasz A. Kurgan, Marek Z. Reformat, Khalid Hafeez:
Fourth International Conference on Machine Learning and Applications, ICMLA 2005, Los Angeles, California, USA, 15-17 December 2005. IEEE Computer Society 2005, ISBN 0-7695-2495-8
Invited Paper
- Stuart Harvey Rubin:
A system of systems (SoS) design amplifier.
Classification I
- Thomas Villmann, Frank-Michael Schleif
, Barbara Hammer
Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning. - Abdul Majid, Asifullah Khan, Anwar M. Mirza
Intelligent combination of kernels information for improved classification. - Senjian An
Fast cross-validation of kernel Fisher discriminant classifiers.
Classification II
- Daisuke Yamaguchi, GuoDong Li, Kozo Mizutani, Takahiro Akabane, Masatake Nagai, Masatoshi Kitaoka:
Decision rule extraction and reduction based on grey lattice classification. - Péter Schönhofen, András A. Benczúr:
Feature selection based on word-sentence relation. - Minoo Aminian:
Active learning for reducing bias and variance of a classifier using Jensen-Shannon divergence. - Ricardo Blanco-Vega, José Hernández-Orallo, M. José Ramírez-Quintana:
Knowledge acquisition through machine learning: minimising expert's effort. - Taghi M. Khoshgoftaar, Jason Van Hulse:
Identifying noise in an attribute of interest.
Applications I
- Mahsa Kamali Moghaddam, Reza Safabakhsh
TASOM-based lip tracking using the color and geometry of the face. - Effrosini Kokiopoulou, Yousef Saad
Face recognition using OPRA-faces. - Alina Lazar, Bradley Shellito:
Comparing machine learning classification schemes - a GIS approach. - Justin M. Beaver, Guy A. Schiavone, Joseph Berrios:
Predicting software suitability using a Bayesian belief network. - M. Arif Wani, Sumia Rashid:
Parallel algorithm for control chart pattern recognition.
Applications II
- Marcos M. Campos, Peter J. Stengard, Boriana L. Milenova:
Data-centric automated data mining. - Marcos M. Campos, Boriana L. Milenova:
Creation and deployment of data mining-based intrusion detection systems in Oracle Database l0g. - Christophe G. Giraud-Carrier
The data mining advisor: meta-learning at the service of practitioners. - Taghi M. Khoshgoftaar, Shyam Varan Nath, Shi Zhong, Naeem Seliya:
Intrusion detection in wireless networks using clustering techniques with expert analysis.
Special Session: Applications of Machine Learning in Medicine and Biology I
- François Fleuret, Wulfram Gerstner
A Bayesian kernel for the prediction of neuron properties from binary gene profiles. - Lit-Hsin Loo, Samuel Roberts, Leonid Hrebien, Moshe Kam:
New filter-based feature selection criteria for identifying differentially expressed genes. 10 - Huimin Geng, Xutao Deng, Hesham H. Ali:
A new clustering algorithm using message passing and its applications in analyzing microarray data. - Li Liao, Robel Y. Kahsay, Guang R. Gao:
Discriminating transmembrane proteins from signal peptides using SVM-Fisher approach. - Roger A. Craig, Li Liao:
Iterative weighting of phylogenetic profiles increases classification accuracy.
Special Session: Applications of Machine Learning in Medicine and Biology II
- Rodrigo A. Vivanco, Aleksander B. Demko, Nick J. Pizzi:
Scopira: a pattern recognition application framework for biomedical datasets. - Mila Kwiatkowska, Anthony S. Atkins, Najib T. Ayas, C. Frank Ryan:
Integrating knowledge-driven and data-driven approaches for the derivation of clinical prediction rules. - Rafal Rak, Lukasz A. Kurgan
Multi-label associative classification of medical documents from MEDLINE.
Special Session: Applications of Machine Learning in Medicine and Biology III
- Ying Liu:
Drug design by machine learning: ensemble learning for QSAR modeling. - Glenn Fung, Maleeha Qazi, Sriram Krishnan, Jinbo Bi, R. Bharat Rao, A. Katz:
Sparse classifiers for Automated HeartWall Motion Abnormality Detection. 194-200 - Júlio C. Nievola, Helyane Bronoski Borges:
Attribute selection methods comparison for classification of diffuse large B-cell lymphoma. - Adam E. Gaweda, Mehmet Kerem Müezzinoglu, George R. Aronoff, Alfred A. Jacobs, Jacek M. Zurada, Michael E. Brier:
Incorporating prior knowledge into Q-learning for drug delivery individualization.
Special Session: Applications of Machine Learning in Medicine and Biology IV
- Mark Schmidt, Ilya Levner, Russell Greiner, Albert Murtha, Aalo Bistritz:
Segmenting brain tumors using alignment-based features. - Valentina Zubek, David Verbel, Olivier Saidi:
Censored Time TreesTM for predicting time to PSA recurrence. - Hui Liu, Ash Kshirsagar, Craig Niederberger:
The application of machine learning techniques to the prediction of erectile dysfunction. - Alireza Tamaddoni-Nezhad
Abduction and induction for learning models of inhibition in metabolic networks. - Iead Rezek, Stephen J. Roberts, Ellini Siva, R. Conradt:
Depth of anaesthesia assessment with generative polyspectral models.
Learning
- Yasutoshi Yajima, Takashi Hoshiba:
Optimization approaches for semi-supervised learning. - Shinichi Hamano:
Equating interestingness of causal rules via graded response theory. - Filip Zelezný
Efficient construction of relational features.
Clustering
- Rasika Amarasiri, Jason Ceddia, Damminda Alahakoon:
Exploratory data mining lead by text mining using a novel high dimensional clustering algorithm. - Gül Nildem Demir, A. Sima Etaner-Uyar
A new graph-based evolutionary approach to sequence clustering. - Ding Zhou, Yang Song, Hongyuan Zha, Ya Zhang:
Towards discovering organizational structure from email corpus. - Ray R. Hashemi, Mahmood Bahar, Christopher Childers, Alexander A. Tyler:
Decoupling of clustering and classification steps in a cluster-based classification.
Text Processing
- Vishwa Vinay, Ingemar J. Cox
A comparison of dimensionality reduction techniques for text retrieval. - Hemant Joshi, Coskun Bayrak:
Learning contextual behavior of text data. - Thammanoon Ditcharoen, Kanlaya Naruedomkul, Nick Cercone, Bundit Tipakorn:
TSTMT: step towards an accurate Thai sign translation. - Catarina Silva
Speeding-up text categorization in a grid computing environment.
Evolutionary-Based Methods
- Ryouei Takahashi:
Solving the traveling salesman problem through genetic algorithms with changing crossover operators. - Shinji Eto, Kotaro Hirasawa, Jinglu Hu:
Switching for functional localization of genetic network programming. - Janaki Gopalan, Emin Erkan Korkmaz
Effective data mining by integrating genetic algorithm into the data preprocessing phase. - Xin Li, Chi Zhou, Weimin Xiao, Peter C. Nelson:
Direct evolution of hierarchical solutions with self-emergent substructures. - Fernando Lozano, Vladimir Koltchinskii:
Self bounding genetic algorithms for machine learning.
Boosting
- Rosa Maria Valdovinos
Class-dependant resampling for medical applications. - Sang Hwa Lee, Hong Il Kim, Nam Ik Cho, Yu Han Jeong, Ki Suk Chung, Chung Sam Jun:
Automatic defect classification using boosting. - Hong Il Kim, Sang Hwa Lee, Nam Ik Cho:
An efficient multicategory classifier based on AdaBoosting. - Fernando Lozano, Pedro Rangel:
Algorithms for parallel boosting. - Pedro Rangel, Fernando Lozano, Elkin García:
Boosting of support vector machines with application to editing.
Associations Learning
- Mehdi Adda
On the discovery of semantically enhanced sequential patterns. - Xiaomeng Wang, Christian Borgelt, Rudolf Kruse:
Fuzzy frequent pattern discovering based on recursive elimination. - Mirko Böttcher, Martin Spott, Detlef D. Nauck:
Detecting temporally redundant association rules. - Aniket Mahanti, Reda Alhajj:
Visual interface for online watching of frequent itemset generation in Apriori and Eclat.
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