next up previous
Next: About this document Up: Learning Comprehensible Descriptions of Previous: Acknowledgements

References

Bengio, 1996
Bengio, Y. (1996). Neural Networks for Speech and Sequence Recognition. International Thomson Publishing Inc.

Danyluk, 1998
Danyluk, A. (1998). Predicting the future: AI approaches to time-series problems. Technical Report WS-98-07, AAAI Press.

Das et al., 1998
Das, G., Lin, K.-I., Mannila, H., Renganathan, G., and Smyth, P. (1998). Rule discovery from time series. In Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98). AAAI Press.

Domingos and Pazzani, 1997
Domingos, P. and Pazzani, M. (1997). On the optimality of the simple bayesian classifier under zero-one loss. Machine Learning, 29:103-130.

Dougherty et al., 1995
Dougherty, J., Kohavi, R., and Sahami, M. (1995). Supervised and unsupervised discretization of continuous features. In Machine Learning: Proceedings of the 12th International Conference on Machine Learning, pages 194-202. Morgan-Kaufmann.

Friedman et al., 1998
Friedman, N., Murphy, K., and Russell, S. (1998). Learning the structure of dynamic probabilistic networks. In Proceeding Uncertainty in Artificial Intelligence Conference 1998 (UAI-98). AAAI Press.

John et al., 1994
John, G. H., Kohavi, R., and Pfleger, K. (1994). Irrelevant features and the subset selection problem. In Proceedings of the International Conference on Machile Learning 1994, pages 121-129.

Johnston, 1989
Johnston, T. (1989). Auslan Dictionary: a Dictionary of the Sign Language of the Australian Deaf Community. Deafness Resources Australia Ltd.

Kadous, 1995
Kadous, M. W. (1995). GRASP: Recognition of Australian sign language using instrumented gloves. Master's thesis, School of Computer Science and Engineering, University of New South Wales.

Keogh and Pazzani, 1998
Keogh, E. J. and Pazzani, M. J. (1998). An enhanced representation of time series which allows fast and accurate classification, clustering and relevance feedback. In [Danyluk, 1998], pages 44-51.

Manganaris, 1997
Manganaris, S. (December 1997). Supervised Classification with Temporal Data. PhD thesis, Computer Science Department, School of Engineering, Vanderbilt University.

Mannila et al., 1995
Mannila, H., Toivonen, H., and Verkamo, A. I. (1995). Discovering frequent episodes in sequences. In Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), pages 210-215.

Oates et al., 1998
Oates, T., Jensen, D., and Cohen, P. R. (1998). Discovering rules for clustering and predicting asynchronous events. In [Danyluk, 1998], pages 73-79.

Paliouras, 1997
Paliouras, G. (1997). Refinement of Temporal Constraints in an Event Recognition System using Small Datasets. PhD thesis, University of Manchester.

Quinlan, 1993
Quinlan, J. R. (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann.

Quinlan, 1998
Quinlan, J. R. (1998). Personal discussion.

Rabiner and Juang, 1986
Rabiner, L. R. and Juang, B. H. (1986). An introduction to hidden markov models. IEEE Magazine on Accoustics, Speech and Signal Processing, 3(1):4-16.

Rosenstein and Cohen, 1998
Rosenstein, M. T. and Cohen, P. R. (1998). Concepts from time series. In AAAI '98: Fifteenth National Conference on Artificial Intelligence, pages 739-745. AAAI, AAAI Press.

Saito, 1994
Saito, N. (1994). Local feature extraction and its application using a library of bases. PhD thesis, Yale University.

Shahar, 1997
Shahar, Y. (1997). A framework for knowledge-based temporal abstraction. Artificial Intelligence, 90(1-2):79-133.

Shahar and Musen, 1995
Shahar, Y. and Musen, M. A. (1995). Knowledge-based temporal abstraction in clinical domains. Technical report, Stanford University.

Zweig and Russell, 1998
Zweig, G. and Russell, S. (1998). Speech recognition with dynamic Bayesian networks. In Fifteenth National Conference on Artificial Intelligence (AAAI'98), pages 173-180. AAAI Press.



Mohammed Waleed Kadous
Wed May 19 20:21:38 EST 1999