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Publicaciones Soportadas por el Proyecto KEEL
  Accountable: Amelia Zafra Gómez (member_email)




Main  Journal Contributions: Published

Jump to Year:   2007  2006  2005  2004  2003  1998  1997



2007

  G. Carneiro, A.B. Chan, P.J. Moreno, N. Vasconcelos. Supervised Learning of semantic classes for image annotation and retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence 29:3 (2007) 394-410   bib
 
  X. Qi, Y. Han. Incorporating multiple SVMs for automatic image annotation. Pattern Recognition 40 (2007) 728-741   Pdf bib
 
  Z.H. Zhou, M.L. Zhang. Solving multi-instance problems with classifier ensemble based on constructive clustering. knowledge and information systems 11:2 (2007) 155-170   bib
 

2006

  Y. Chen, J. Bi, J.Z. Wang. MILES: Multiple-Instance Learning via Embedded Instance Selection. IEEE Transactions on Pattern Analysis and Machine Intelligence 28:12 (2006) 1931-1947   bib
 
  S.C. Chen, S.H. Rubin, M.L. Shyu, C. Zhang. A dynamic user concept pattern learning framework for content-based image retrieval. IEEE Transaction on System Man Cybernetics Part C Applications and Reviews 36:6 (2006) 772-783   Pdf bib
 
  H.-B. Dai, M.-L. Zhang, Z.-H. Zhou. A multi-instance learning based approach to image retrieval. Pattern Recognition and Artificial 19:2 (2006) 179-185   bib
 
  D.R. Dooly, S.A. Goldman, S.S. Kwek. Real-valued multiple-instance learning with queries. Journal of Computer and System Sciences 72 (2006) 1-15   Pdf bib
 
  M.-L. Zhang, Z.-H. Zhou. Adapting RBF neural networks to multi-instance learning. Neural Processing Letters 23:1 (2006) 1-26   Pdf bib
 
  Z.-H. Zhou. Multi-instance learning from supervised view. Journal of Computer Science and Technology 21:5 (2006) 800-809   Pdf bib
 

2005

  J.F. Murray, G.F. Hughes, K. Kreutz-Delgado. Machine learning methods for predicting failures in hard drives: A multiple-instance application. ournal of Machine Learning Research 6 (2005) 783-816   Pdf bib
 
  S. Scott, J. Zhang, J. Brown. On Generalized Multiple-Instance Learning. International Journal of Computational Intelligence and Applications 5:1 (2005) 21-35   bib
 
  Z.-H. Zhou, K. Jiang, M. Li. Multi-instance learning based web mining. Applied Intelligence 22:2 (2005) 135-147   Pdf bib
 

2004

  M.-L. Zhang, Z.-H. Zhou. Improve Multi-Instance Neural Networks through Feature Selection. Neural Process Letters 19:1 (2004) 1-10   Pdf bib
 

2003

  D.R. Dooly, Q. Zhang, S.A. Goldman, R.A. Amar. Multiple-instance learning of real-valued data. Journal of Machine Learning Research 3 (2003) 651-678   Pdf bib
 
  S.A. Goldman, S.D. Scott. Multiple-instance learning of real-valued geometric patterns. Annals of Mathematics and Artificial Intelligence 39:3 (2003) 259-290   Pdf bib
 

1998

  A.L. Blum, A. Kalai. A Note on Learning from Multiple-Instance Examples. Machine Learning 30 (1998) 23-29   bib
 
  P.M. Long, L. Tan. PAC Learning Axis-aligned Rectangles with Respect to Product Distributions from Multiple-Instance Examples. Machine Learning 30 (1998) 7-21   bib
 

1997

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Main  Conference Contributions

Jump to Year:   2007  2006  2005  2004  2003  2002  2001  1998



2007

  R.C. Bunescu, R.J. Mooney. Multiple Instance Learning for Sparse Positive Bags. 24th International Conference on Machine Learning (ICML2007). Omni Press. Corvallis OR (USA, 2007) 0-0   Pdf bib
 

2006

  P.-M. Cheung, J.T. Kwok. A regularization framework for multiple-instance learning. 23rd International Conference on Machine Learning (ICML). Pittsburgh (Pennsylvania, 2006) 193-200   Pdf bib
 
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  D. Wang, J. Li, B. Zhang. Multiple-instance learning via random walk. 17th European Conference on Machine Learning (ECML). Lecture Notes in Computer Science 4212, Springer-Verlag 2006, Berlin (Germany, 2006) 473-473   Pdf bib
 
  C. Yang. Region-based image annotation using asymmetrical support vector machine-based multiple-instance learning. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR). New York (EEUU, 2006) 2057-2063   Pdf bib
 

2005

  S.C. Chuang, Y.Y. Xu, H.-C. Fu. Neural network based image retrieval with multiple instance leaning techniques. 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES). Melbourne (Australia, 2005) 1210-1216   Pdf bib
 
  M.R. Naphade, J.R. Smith. A generalized multiple instance learning algorithm for large scale modeling of multimedia semantics. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). Philadelphia (PA, 2005) 341-344   Pdf bib
 
  S. Ray, M. Craven. Supervised versus multiple instance learning: An empirical comparison. 22nd International Conference on Machine Learning (ICML). Bonn (Germany, 2005) 697-704   Pdf bib
 
  C. Schmid, S. Soatto, C. Tomasi. Formulating semantic image annotation as a supervised learning problem. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ). San Diego (CA, 2005) 163-168   Pdf bib
 
  C. Zhang, X. Chen, M. Chen, S.-C. Chen, M.-L. Shyu. A multiple instance learning approach for content based image retrieval using one-class support vector machine. IEEE International Conference on Multimedia and Expo (ICME). Amsterdam (Netherlands, 2005) 1142-1145   Pdf bib
 
  C. Zhang, X. Chen. Region-based image clustering and retrieval using multiple instance learning. 4th International Conference on Image and Video Retrieval (CIVR). Singapore (Malaysian, 2005) 194-204   Pdf bib
 
  Z.-H. Zhou, X.-B. Xue, Y. Jiang. Locating regions of interest in CBIR with multi-instance learning techniques. 18th Australian Joint Conference on Artificial Intelligence (AI). Lecture Notes in Computer Science 3809, Springer-Verlag 2005, Sydney ( Australia, 2005) 92-101   Pdf bib
 

2004

  Q. Tao, S. Scott, N.V. Vinodchandran, T.T. Osugi. SVM-based generalized multiple-instance learning via approximate box counting. 21st International Conference on Machine Learning (ICML). Banff (Alta, 2004) 799-806   Pdf bib
 
  S. Andrews, T. Hofmann. Multiple Instance Learning via Disjunctive Programming Boosting. Advances in Neural Information Processing Systems 2003 (NIPS 16). Cambridge (USA, 2004) 65-72   bib
 
  P. Auer, R. Ortner. A boosting approach to multiple instance learning. 15th European Conference on Machine Learning (ECML). Lecture Notes in Computer Science 3201, Springer-Verlag 2004, Pisa (Italy, 2004) 63-74   Pdf bib
 
  P. Reutemann, B. Pfahringer, E. Frank. A toolbox for learning from relational data with propositional and multi-instance learners. 17th Australian Joint Conference on Artificial Intelligence (AI). Lecture Notes in Computer Science 3339, Springer-Verlag 2004, Cairns (Australia, 2004) 1017-1023   Pdf bib
 
  Q. Tao, S.D. Scott,. A faster algorithm for generalized multiple-instance learning. 17th International Florida Artificial Intelligence Research Society Conference (FLAIRS). Miami Beach (Florida, 2004) 550-555   Pdf bib
 

2003

  A. McGovern, D. Jensen. Identifying Predictive Structures in Relational Data Using Multiple Instance Learning. 20th International Conference on Machine Learning (ML). Washington (DC, 2003) 528-535   Pdf bib
 
  N. Weidmann, E. Frank, B. Pfahringer. A Two-Level Learning Method for Generalized Multi-instance Problems. European Conference on Machine Learning (ECML 2003). Lecture Notes in Computer Science 2837, Springer 2003, Cavtat Dubrovnik (Croatia, 2003) 468-479   bib
 
  Z.-H. Zhou, M.-L. Zhang, K.-J. Chen. A Novel Bag Generator for Image Database Retrieval with Multi-Instance Learning Techniques. 15th IEEE International Conference on Tools with artificial Intelligence. Sacramento (CA, 2003) 565-569   Pdf bib
 
  Z.-H. Zhou, M.-L. Zhang. Ensembles of multi-instance learners. 14th European Conference on Machine Learning (ML). Cavtat (Dubrovnik, 2003) 492-502   Pdf bib
 

2002

  S. Andrews, T. Hofmann. Multiple instance learning with generalized support vector machines. 18th National Conference on Artificial Intelligence (AAAI). Edmonton (Alta, 2002) 943-944   Pdf bib
 
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2001

  Y. Chevaleyre, J.-D. Zucker. Solving Multiple-Instance and Multiple-Part Learning Problems with Decision Trees and Rule Sets. Application to the Mutagenesis Problem. 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence (AI). Lecture Notes in Computer Science 2056, Springer-Verlag 2001, London (UK, 2001) 204-214   Pdf bib
 
  Y. Chevaleyre, J.D. Zucker. A Framework for Learning Rules from Multiple Instance Data. European Conference on Machine Learning (ECML 2001). Lecture Notes in Computer Science 2167, Springer 2001, Freiburg (Germany, 2001) 49-60   Pdf bib
 

1998

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     Amelia Zafra Gómez (member_email)



 
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