Journal Papers

H.T. Lin and
L. Li.
Support Vector Machinery for Infinite Ensemble Learning.
Journal of Machine Learning Research, 9(2), 285312, 2008.
(Official Version).

H.T. Lin,
C.J. Lin,
and
R. C. Weng.
A Note on Platt's Probabilistic Outputs for Support Vector
Machines.
Machine Learning, 68(3), 267276, 2007.
(Code),
(Official Version).

S.P. Liao,
H.T. Lin, and
C.J. Lin.
A Note on the Decomposition Methods for Support Vector Regression.
Neural
Computation, 14(6), 12671281, 2002. (a shorter version appeared in IJCNN '01).
(Official Version).
PeerReviewed Conference and Workshop Papers

L. Li and
H.T. Lin.
Optimizing 0/1 Loss for Perceptrons
by Random Coordinate Descent.
In Proceedings of IJCNN '07, 749754, IEEE, 2007.
(Talk).

L. Li and
H.T. Lin.
Ordinal Regression by Extended Binary Classification.
In B. Schölkopf et al., eds., Advances in Neural Information Processing Systems:
Proceedings of the 2006 Conference
(NIPS '06),
865872, MIT Press, 2007.
(Code),
(Spotlight),
(Poster).

H.T. Lin and
L. Li.
LargeMargin Thresholded Ensembles for Ordinal Regression: Theory and Practice.
In J. Balcazár et al., eds., Algorithmic Learning Theory:
ALT '06,
vol. 4264
of Lecture Notes in Artificial Intelligence,
319333, SpringerVerlag, 2006.
(Talk),
(Code).

H.T. Lin and
L. Li.
Novel DistanceBased SVM Kernels for Infinite Ensemble Learning.
In Proceedings of ICONIP '05, 761766, 2005.
(Talk),
(Code).

H.T. Lin and
L. Li.
Analysis of SAGE Results with Combined Learning Techniques.
In P. Berka and B. Crémilleux, eds.,
Proceedings of the
ECML/PKDD
2005 Discovery Challenge,
102113, 2005.
(Talk).

H.T. Lin and
L. Li.
Infinite Ensemble Learning with Support Vector Machines.
In J. Gama et al., eds., Machine Learning:
ECML '05,
vol. 3720
of Lecture Notes in Artificial Intelligence,
242254, SpringerVerlag, 2005.
(Talk),
(Code).

L. Li,
A. Pratap,
H.T. Lin and
Y. S. AbuMostafa.
Improving Generalization by Data Categorization.
In A. Jorge et al., eds., Knowledge Discovery in Databases:
PKDD '05,
vol. 3721
of Lecture Notes in Artificial Intelligence,
157168, SpringerVerlag, 2005.
(Code).

S.P. Liao,
H.T. Lin, and
C.J. Lin.
A Note on the Decomposition Methods for Support Vector Regression.
In Proceedings of IJCNN '01, 14741479, IEEE/Omnipress, 2001.
Thesis

H.T. Lin.
Infinite Ensemble Learning with Support
Vector Machines.
Master's Thesis, California Institute of Technology, May 2005.
(Caltech ETD),
(Updated PDF),
(Code).
Technical Report
Feel free to contact me: "htlin" at "csie.ntu.edu.tw"