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| In the second part of the course, we will read and discuss the following papers: |
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| Time slot |
Student(s) |
Paper(s) |
Nov 30 (9:40-10:30)
|
Gultekin/Kullu |
S. Salzberg, "On comparing classifiers: Pitfalls to avoid and a recommended approach,"
Data Mining and Knowledge Discovery, 1:317-327, 1997. |
Dec 2 (10:40-11:30)
|
Aydin/Saritas |
J. Demsar, "Statistical comparisons of classifiers over multiple data sets," Journal of Machine Learning
Research, 7:1-30, 2006. |
Dec 7 (8:40-9:30)
|
Ozbek/Taylan |
A.T. Lasko, J.G. Bhagwat, K.H. Zou, L. Ohno-Machado, "The use of receiver operating characteristic curves
in biomedical informatics," Journal of Biomedical Informatics, 38:404-415, 2005. |
Dec 7 (9:40-10:10)
|
Bayir |
P. Turney, "Types of cost in inductive concept learning," Proceedings of Workshop on Cost-Sensitive Learning at the
17th International Conference on Machine Learning, 15-21, 2000. |
Dec 7 (10:10-10:30)
|
Ekmekci |
C. Elkan, "The foundations of cost-sensitive learning," Proceedings of the Seventeenth International
Joint Conference on Artificial Intelligence, 2001. |
Dec 9 (10:40-12:00)
|
Ercan/Erdem/Toraman |
R. Polikar, "Ensemble based systems in decision making," IEEE Circuits and Systems Magazine, 6(3):21-45, 2006. |
Dec 14 (8:40-9:30)
|
Mergenci/Terzi |
Y. Sun, M.S. Kamel, A.K.C. Wong, Y. Wang, "Cost-sensitive boosting for classification of
imbalanced data," Pattern Recognition, 40(12):3358-3378, 2007. |
Dec 14 (9:40-10:30)
|
Sari/Sevim |
R.E. Schapire, Y. Singer, "BoosTexter: A boosting-based system for text categorization,"
Machine Learning, 39:135-168, 2000. |
Dec 16 (10:40-11:10)
|
Dinc |
K.-R. Muller, S. Mika, G. Ratsch, K. Tsuda, B. Scholkopf, "An introduction to kernel-based learning algorithms,"
IEEE Transactions on Neural Networks, 12(2):181-201, 2001 (read only the first seven pages). |
Dec 16 (11:10-11:30)
|
Guvercin |
G. Rubio, H. Pomares, L.J. Herrera, I. Rojas, "Kernel methods applied to time series forecasting,"
Proceedings of the 9th International Work Conference on Artificial Neural Networks, 2007. |
Dec 21 (8:40-9:30)
|
Samet/Sener |
Y.Y. Lin, T.L. Liu, C.S. Fuh, "Multiple kernel learning for dimensionality reduction," IEEE Transactions on
Pattern Analysis and Machine Intelligence, 33(6):1147-1160, 2011. |
Dec 21 (9:40-10:10)
|
Uyanik |
L. Ladicky, P. Torr, "Locally linear support vector machines," Proceedings of the 28th International
Conference on Machine Learning, 2011. |
Dec 23 (10:40-11:30)
|
Gokden/Hamzacebi |
D. Cohn, Z. Ghahramani, M. Jordan, "Active learning with statistical models,"
Journal Artificial Intelligence Research, 4:129-145, 1996. |
Dec 28 (8:40-9:30)
|
Aman/Mercan |
D. Tuia, F. Ratle, F. Pacifici, M.F. Kanevski, W.J. Emery, "Active learning methods for remote
sensing image classification," IEEE Transactions on Geoscience and Remote Sensing, 47(7):2218-2232, 2009. |
Dec 28 (9:40-10:30)
|
Kerimoglu/Yavuzer |
S. Tong, D. Koller, "Support vector machine active learning with applications to text classification,"
Journal of Machine Learning Research, 2:45-66, 2001. |
Dec 30 (10:40-11:30)
|
Karakuzu/Sazoglu |
R. Caruana, "Multitask learning," Machine Learning, 28(1):41-70, 1997. |
Jan 4 (8:40-9:30)
|
Aytas/Sahin |
S.J. Pan, Q. Yang, "A survey on transfer learning," IEEE Transactions on
Knowledge and Data Engineering, 22(10):1345-1359, 2010. |
Jan 4 (9:40-10:30)
|
Gur/Senol |
M. Neuhaus, K. Riesen, H. Bunke, "Novel kernels for error-tolerant graph classification,"
Spatial Vision, 22(5):425-441, 2009. |
Jan 6 (10:40-11:30)
|
Eravci/Eser |
I. Tsochantaridis, T. Joachims, T. Hofmann, Y. Altun, "Large margin methods for structured and interdependent
output variables," Journal of Machine Learning Research 6:1453-1484, 2005. |
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