Dr. C. Lee Giles

Publications before Penn State

Fairly complete publications: 1992-1999, see New Stuff for 2000-present publications.

For copies of any untrievable papers, please contact Lee Giles.

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What's here:

• Refereed Journal Papers
• Refereed Conference Papers
• Edited Books & Book Chapters
• Edited Proceedings and Special Issues
• Edited Letters to the Editor
• Old Technical Reports
• Bibliography in latex bib file format of most of the older publications

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Refereed Journal Papers: 

• C.L. Giles, C.W. Omlin, K. K. Thornber, "Equivalence in Knowledge Representation: Automata, Recurrent Neural Networks, and Dynamical Fuzzy Systems," Proceedings of the IEEE, 87(9), 1999. 
• S. Lawrence, C.L. Giles, "Accessibility of Information on the Web," Nature, 400, 107-109, 1999.
• S. Lawrence, C.L. Giles, “Searching the Web: General and Scientific Information Access," IEEE Communications, Special issue on "Digital Library Using Next Generation Internet," 37(1), p 116, 1999.
• A. Back, B. Horne, C.L. Giles, A-C. Tsoi, "Alternative Discrete-Time Operators: An Algorithm for Optimal Selection of Parameters," IEEE Transactions on Signal Processing 47(9), 2612-2615, 1999.
• Steve Lawrence, C. Lee Giles, K. Bollacker, "Digital Libraries and Autonomous Citation Indexing," IEEE Computer, 32(6), 67-71, 1999
• S. Lawrence, C.L. Giles, "Context and Page Analysis for Improved Web Search," IEEE Internet Computing, 2(4), 38-46, 1998.
• Rembrandt Bakker, Jaap C. Schouten, C. Lee Giles, Floris Takens, Cor M. van den Bleek, "Learning Chaotic Attractors by Neural Networks," Neural Computation 12(10), 2355-2383, 2000.
• S. Lawrence, C.L. Giles, S. Fong, "Natural Language Grammatical Inference with Recurrent Neural Networks," IEEE Trans. on Knowledge and Data Engineering, 12(1), 126-140, 2000.
• The labeled corpus used in this study.
• T. Lin, B.G. Horne, C.L. Giles, "How Embedded Memory in Recurrent Neural Network Architectures Helps Learning Long-term Temporal Dependencies," Neural Networks 11(5), p. 861, 1998.
• S. Lawrence, C.L. Giles, "Searching the World Wide Web," Science, 280(5360), 98-100, 1998.
• C.W. Omlin, K.K. Thornber, C.L. Giles, "Fuzzy Finite-State Automata Can Be Deterministically Encoded Into Recurrent Neural Networks,"  IEEE Trans. on Fuzzy Systems, 6(1), p. 76, 1998.
• S. Lawrence, A. Back, A-C. Tsoi, C.L. Giles, "On the Distribution of Performance from Multiple Neural Network Trials," IEEE Trans. Neural Networks, 8(6), p. 1507, 1997.
• D.S. Clouse, C.L. Giles, B.G. Horne, G.W. Cottrell, "Time-Delay Neural Networks: Representation and Induction of Finite State Machines," IEEE Trans. on Neural Networks, 8(5), p. 1065, 1997.
• T. Lin, C.L. Giles, B.G. Horne, S.Y. Kung, "A Delay Damage Model Selection Algorithm for NARX Neural Networks," IEEE Trans., on Signal Processing, "Special Issue on Neural Networks," 45(11), p. 2719, 1997. (IEEE SIGNAL PROCESSING SOCIETY 1998 YOUNG AUTHOR BEST PAPER AWARD)
• H. Siegelmann, C.L.Giles, "The Complexity of Language Recognition by Neural Networks," Neurocomputing, Special Issue on "Recurrent Networks for Sequence Processing," Eds: M. Gori, M. Mozer, A.H. Tsoi, W. Watrous, vol. 15, p. 327, 1997.
• H. T. Siegelmann, B.G. Horne, C.L. Giles, "Computational capabilities of recurrent NARX neural networks," IEEE Trans. on Systems, Man and Cybernetics--Part B: Cybernetics, 27(2), p. 208, 1997.
• Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, Andrew D. Back, "Face Recognition: A Convolutional Neural Network Approach," IEEE Trans. on Neural Networks, 8(1), p. 98, 1997.
• T. Lin, B.G. Horne, P. Tino, C.L. Giles, "Learning long--term dependencies in NARX recurrent neural networks," IEEE Trans. on Neural Networks, 7(6), p. 1329, 1996. (OUTSTANDING PAPER AWARD for 1996 IEEE TRANSACTIONS ON NEURAL NETWORKS)
• C.W. Omlin, C.L. Giles, "Constructing Deterministic Finite-State Automata in Recurrent Neural Networks," Journal of the ACM, 45(6), 937-972, 1996.
• Kam Jim, C.L. Giles, B.G. Horne, "Synaptic Noise in Dynamically-driven Recurrent Neural Networks: Convergence and Generalization," IEEE Trans. on Neural Networks, 7(6), p. 1424, 1996.
• C.W. Omlin, C.L. Giles, "Stable Encoding of Large Finite-State Automata in Recurrent Neural Networks with Sigmoid Discriminants," Neural Computation, 8(4), p. 675, 1996.
• C.W. Omlin, C.L. Giles, "Extraction of Rules from Discrete-Time Recurrent Neural Networks," Neural Networks, 9(1), 41-52, 1996.
• C.W. Omlin, C.L. Giles, "Rule Revision with Recurrent Neural Networks," IEEE Trans. on Knowledge and Data Engineering, 8(1), pp. 183-188, 1996.
• C.L. Giles, B.G. Horne, T. Lin, "Learning a Class of Large Finite State Machines with a Recurrent Neural Network," Neural Networks, 8(9), 1359-1365, 1995.
• M.W. Goudreau, C.L. Giles, "Using Recurrent Neural Networks to Learn the Structure of Interconnection Networks," Neural Networks, 8(5), 793-804, 1995.
• C.L. Giles, M.W. Goudreau, "Routing in Optical Multistage Interconnection Networks: A Neural Network Solution," IEEE/OSA J. of Lightwave Technology, Special Issue on Optical Interconnections for Information Processing, 13(6), p. 1111, 1995.
• C.L. Giles, D. Chen, G.Z. Sun, H.H. Chen, Y.C. Lee, M.W. Goudreau, "Constructive Learning of Recurrent Neural Networks: Problems with Recurrent Cascade Correlation and a Simple Solution," IEEE Trans. on Neural Networks, 6(4), p. 829, 1995.
• C. L. Giles, C.W. Omlin, "Pruning Recurrent Neural Networks for Improved Generalization Performance, "IEEE Trans. on Neural Networks, 5(5), p. 848, 1994.
• M.W. Goudreau, C.L. Giles, S.T. Chakradhar, D. Chen, "First-Order Vs. Second-Order Single Layer Recurrent Neural Networks,"IEEE Trans. on Neural Networks, 5 (3), p. 511, 1994.
• C.L. Giles, G.M. Kuhn, R.J. Williams (Guest Editors) - Special Issue on "Dynamical Recurrent Neural Networks," IEEE Trans. on Neural Networks, 5(2), 1994.  bib.file of special issue
• C.B. Miller, C.L. Giles, "Experimental Comparison of the Effect of Order in Recurrent Neural Networks," International Journal of Pattern Recognition and Artificial Intelligence, (Special Issue on Neural Networks), 7(4), p. 849, 1993.
• C.L. Giles, C.W. Omlin, "Extraction, Insertion and Refinement of Production Rules in Recurrent Neural Networks," Connection Science, Special Issue on "Architectures for Integrating Symbolic and Neural Processes", 5(3-4), p.307, 1993.
• C.L. Giles, C.B. Miller, D. Chen, H.H. Chen, G.Z. Sun, Y.C. Lee, "Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks," Neural Computation, 4(3), p. 393, 1992.
• M.W. Goudreau, C.L. Giles, "Routing in Random Multistage Interconnection Networks: Comparing Exhaustive Search, Greedy and Neural Network Approaches," International Journal of Neural Systems, 3(2), 1992.

Refereed Conference Papers:

• K. Bollacker, S. Lawrence, C.L. Giles, "A System For Automatic Personalized Tracking of Scientific Literature on the Web," DL'99 Digital Libraries, The 4th ACM Conference on Digital Libraries, 105-113, 1999.
• E.J. Glover, S. Lawrence, M.D. Gordon, W.P. Birmingham, C.L Giles, "Recommending Web Documents Based on User Preferences," Proceedings of the ACM SIGIR '99 Workshop on Recommender Systems: Algorithms and Evaluation, 1999.
• S. Lawrence, C.L. Giles, K. Bollacker, "Scientific Literature Indexing on the Web," Poster Proceedings of the 8th International World Wide Conference,  120-121, 1999.
• S. Lawrence, C.L. Giles, K. Bollacker, "Autonomous Citation Matching, "Proceedings of the 3rd ACM Annual Conference on Autonomous Agents (poster),  392-393, 1999.
• S. Lawrence, C.L. Giles, "Text and Image Metasearch on the Web, "International Conference on Parallel and Distributed Processing Techniques and Applications, CSREA Press, 829-835, 1999.
• E.J. Glover, S. Lawrence, W.P. Birmingham, C.L. Giles, "Architecture of a Metasearch Engine that Supports User Information Needs," Eighth International Conference on  Information and Knowledge Management (CIKM’99), 210-216, 1999.
• S. Lawrence, K. Bollacker, C.L. Giles, "Indexing and Retrieval of Scientific Literature on the Web," Eighth International Conference on  Information and Knowledge Management (CIKM’99), 139-146, 1999.
• Rembrandt Bakker, Jaap C. Schouten, Marc-Olivier Coppens, Floris Takens, C. Lee Giles, Cor M. van den Bleek, "Robust Learning of Chaotic Attractors," Advances in Neural Information Processing Systems, NIPS 1999, 879-885, 1999.
  
•  C.L. Giles, K. Bollacker, S. Lawrence, "CiteSeer: An Automatic Citation Indexing System," DL'98 Digital Libraries, 3rd ACM Conference on Digital Libraries, pp. 89-98, 1998. [ONE OF EIGHT PAPERS SELECTED FOR BEST PAPER AWARD].
• K. Bollacker, S. Lawrence, C.L. Giles, "CiteSeer: An Autonomous Web Agent for Automatic Retrieval and Identification of Interesting Publicatiions,"  Agents'98, 2nd International ACM Conference on Autonomous Agents, 116-123,  1998.
• U. Cetintemel, B.T. Jonsson, Michael J. Franklin, C. Lee Giles, and D. Srivastava, “Evaluating Answer Quality/Efficiency Tradeoffs,” Proceedings of the 5th International Workshop on Knowledge Representation Meets Databases (KRDB'98), p. 19, 1-4, Seattle, 1998.
• M.F. Sakr, S.P. Levitan, C.L. Giles, D.M. Chiarulli, "Reconfigurable Processor Employing Optical Channels," Optics in Computing, OC'98, Proceedings of the SPIE, vol. 3490, p. 564, 1998.
• S. Lawrence. C.L. Giles, "The Inquirus Meta Search Engine," 7th International World Wide Web Conference, 95-105, 1998.
• C.L. Giles, T. Lin, B.G. Horne, S-Y. Kung, "The Past Is Important: A Method for Determining Memory Structure in NARX Neural Networks," IEEE World Conference on Computational Intelligence, p. 1834, 1998.
• R. Bakker, J.C. Schouten, C.M. van der Bleek, C.L. Giles, "Neural Learning of Chaotic Dynamics: The Error Propagation Algorithm," IEEE World Conference on Computational Intelligence, p. 2483, 1998.
• T. Lin, C.L. Giles, B.G. Horne, "What to Remember, How Memory Order Affects the Performance of NARX Neural Networks," IEEE World Conference on Computational Intelligence, p. 1051, 1998.
• Back, B.G. Horne, A. C. Tsoi, C.L. Giles, "Low Sensitivity Time Delay Neural Networks with Cascade Form Structure," Neural Networks for Signal Processing VII, Proceedings of the 1997 IEEE Workshop, IEEE Press, p. 44, 1997.
• C.L. Giles, T. Lin, B.G. Horne, "Remembering the Past: The Role of Embedded Memory in Recurrent Neural Network Architectures," Neural Networks for Signal Processing VII, Proceedings of the 1997 IEEE Workshop, IEEE Press, p. 34, 1997.
• S. Lawrence, A. Back, A-C. Tsoi, C.L. Giles, "The Gamma MLP - Using Multiple Temporal Resolutions for Improved Classification," Neural Networks for Signal Processing VII, Proceedings of the 1997 IEEE Workshop, IEEE Press, p. 256, 1997.
• C.L. Giles, S. Lawrence, A-C. Tsoi, "Rule Inference for Financial Prediction using Recurrent Neural Networks," Proceedings of the IEEE/IAFE Conf. on Computational Intelligence for Financial Engineering, p. 253, IEEE, 1997.
• M.F. Sakr, S.P. Levitan, D.M. Chiarulli , B.G. Horne, C.L. Giles, "Predicting Multiprocessor Memory Access Patterns with Learning Models," Proceedings of the Fourteenth International Conference on Machine Learning, Ed. D. Fisher, p. 305-312, Morgan Kaufmann, 1997.
• S. Lawrence, C.L. Giles, A-C. Tsoi, "Lessons in Neural Network Training: Overfitting may be harder than expected," Proceedings of the 14th AAAI, p. 362, MIT Press, 1997.
• L. Kuvayev, C.L. Giles, H. Cejtin, J. Philbin, "Intelligent Methods for File System Optimization," Proceedings of the 14th AAAI, p. 528, MIT Press, 1997.
• C.L. Giles, Steve Lawrence, "Presenting and Analyzing the Results of AI Experiments: Data Averaging and Data Snooping," Proceedings of the 14th AAAI, p. 540, MIT Press, 1997.
• M.F. Sakr, C.L. Giles, S.P. Levitan, B.G. Horne, M. Maggini, D.M. Chiarulli, "On-Line Prediction of Multiprocessor Memory Access Patterns," Proceedings of the IEEE International Conference on Neural Networks, p. 1564,  1996, BEST PAPER AWARD.
• M.F. Sakr, S.P. Levitan, C.L. Giles, D.M. Chiarulli, B.G. Horne, M. Maggini, "Predictive Control of Opto-Electronic Reconfigurable Interconnection Networks Using Neural Networks," 2nd International Conference on Massively Parallel Processing Using Optical Interconnections, (ed.) E. Schenfeld, 326-335, IEEE Computer Society Press, 1995.
• B.G. Horne, C.L. Giles, "An Experimental Comparison of Recurrent Neural Networks," Advances in Neural Information Processing Systems 7, eds: G. Tesauro, D. Touretzky, T. Leen, p. 697, MIT Press, 1995.
• L.R. Leerink, C.L. Giles, B.G. Horne, M.A. Jabri, "Learning with Product Units," Advances in Neural Information Processing Systems 7, Eds: G. Tesauro, D. Touretzky, T. Leen, p. 537, MIT Press, 1995.
• K. Jim, C. L. Giles, B. G. Horne, "Effects of Noise on Convergence and Generalization in Recurrent Networks," Advances in Neural Information Processing Systems 7, Eds: G. Tesauro, D. Touretzky, T. Leen, p. 649, MIT Press, 1995.
• C.L. Giles, B.G. Horne, "Representation and Learning in Recurrent Neural Network Archi tectures," Proceedings of the Eighth Yale Workshop on Adaptive and Learning Systems, p. 128, 1994.
• C.W. Omlin, C.L. Giles, B.G. Horne, L.R. Leerink, T. Lin, "Training Recurrent Neural Networks with Temporal Input Encodings," IEEE In ternational Conference on Neural Networks (ICNN'94), p. 1267, 1994.
• C.W. Omlin and C.L. Giles, "Constructing Deterministic Finite-State Automata in Sparse Recurrent Neural Networks," IEEE International Conference on Neural Networks (ICNN'94), p. 1732, 1994.
• M.W. Goudreau, C.L. Giles, "Discovering the Structure of a Self Routing Interconnection Network with a Recurrent Neural Network," Proceedings of the International Workshop on Neural Network Applications in Telecommunications, Eds. J. Alspector, R. Goodman, T.X. Brown, Lawrence Erlbaum, Hillsdale, NJ, p. 52, 1993.
• S. Das, C.L. Giles, G.Z. Sun, "Using Prior Knowledge in a NNPDA to Learn Context-Free Languages," Advances in Neural Information Processing Systems 5, S.J. Hanson, J.D. Cowan, C.L. Giles (eds), Morgan Kaufmann, San Mateo, Ca., p. 65, 1993.
• M.W. Goudreau and C.L. Giles, "On recurrent neural networks and representing finite state recognizers," Third International Conference on Artificial Neural Networks, Institution of Electrical Engineers, London, UK, p. 55, 1993.
• D. Chen, C.L. Giles, G.Z. Sun, H.H. Chen, Y.C. Lee, M.W. Goudreau, "Constructive Learning of Recurrent Neural Networks," 1993 IEEE International Conference on Neural Networks, March 28 - April 1, vol III, p. 1196, 1993.
• C.L. Giles, M.W. Goudreau, "A Neural Network Router for Optical Interconnection Networks," OSA 1993 Technical Digest Optical Computing, Series Vol 7, OTuA8, 1993.
• H.T. Siegelmann, E.D. Sontag, C.L. Giles, "The Complexity of Language Recognition by Neural Networks," Algorithms, Software, Architecture, (Ed) J. van Leeuwen, Series - Information Processing 92, Vol 1, Elsevier, Amsterdam, p. 329-335, 1992.
• C.L. Giles, C.W. Omlin, "Inserting Rules into Recurrent Neural Networks," Neural Networks for Signal Processing II, Proceedings of the 1992 IEEE Workshop, eds. S.Y. Kung, F. Fallside, J. Aa. Sorenson, C.A. Kamm, IEEE Press, p. 13, 1992.
• D. Chen, C.L. Giles G. Z. Sun, H. H. Chen, Y.C. Lee, "Learning Finite State Transactionsducers with a Recurrent Neural Network," IJCNN International Joint Conference on Neural Networks, Beijing, China, Vol 1, p. 129, Publishing House of Electronics Industry, Beijing, 1992.
• S. Das, C.L. Giles, G.Z. Sun, "Learning Context Free Grammars: Limitations of a Recurrent Neural Network with an External Stack Memory," Proceedings of the 14 Annual Conference of the Cognitive Science Society, Morgan Kaufmann, San Mateo, p. 79, 1992.
• C.W. Omlin, C.L. Giles, C.B. Miller, "Heuristics for the Extraction of Rules from Discrete-Time Recurrent Neural Networks," Proceedings of the International Joint Conference on Neural Networks, IEEE-92CH3114-6, vol I, p. 33, 1992.
• C.W. Omlin, C. L. Giles, "Training Second-Order Recurrent Neural Networks Using Hints," Proceedings of the 9th International Conference on Machine Learning, eds. D. Sleeman and P. Edwards, Morgan Kaufmann Publishers, San Mateo, CA, p. 363, 1992.
• C.L. Giles, C.B. Miller, D. Chen, G.Z. Sun, H.H. Chen, Y.C. Lee, "Extracting and Learning an Unknown Grammar with Recurrent Neural Networks," Advances in Neural Information Processing Systems 4, eds. J.E. Moody, S.J. Hanson and R.P. Lippmann, Morgan Kaufmann, San Mateo, Ca., p. 317, 1992.
• M.W. Goudreau, C.L.Giles, "Neural Network Routing for Random Multiple Stage Interconnection Networks," Neural Information Processing Systems 4, Morgan Kaufmann Publishers, eds. J.E. Moody, S.J. Hanson, R.P. Lippmann, p.722, 1992.

Reprinted Papers, Edited Books & Book Chapters:

• T. Lin, B.G. Horne, P. Tino, C.L. Giles, “Learning long--term dependencies with NARX networks,” IEEE Trans. on Neural Networks, 7(6), p. 1329, 1996. Reprinted in Recurrent Neural Networks: Design and Applications, (eds) L.C. Jain, L. Medsker, CRC Press, 1999.
• S. Lawrence, C.L. Giles, Context and Page Analysis for Improved Web Search, IEEE Internet Computing, 2(4), pp. 38-46, 1998. Reprinted in: The Journal of the Image Electronics Engineers of Japan, 1999 (in Japanese).
• S. Lawrence, I. Burns, A.D. Back, A.C. Tsoi, C.L. Giles,” Neural Network Classification and Unequal Prior Class Probabilities,” in Tricks of the Trade: Lecture Notes in Computer Science State-of-the-Art Surveys, (eds) G. Orr, K.-R. Muller, R. Caruana, Springer Verlag, 1998.
• C. Lee Giles, M. Gori, Adaptive Processing of Sequences and Data Structures, Lecture Notes in Artificial Intelligence, Springer Verlag, 1998.
• S. Lawrence, C.L. Giles, A-C. Tsoi, “Symbolic Conversion, Grammatical Inference and Rule Extraction for Foreign Exchange Rate Prediction,” Neural Networks in the Capital Markets NNCM96, (eds) Y. Abu-Mostafa, A.S. Weigend, A.-P. N. Refenes, World Scientific Press, Singapore, p. 333, 1998.
• P. Tino, B.G. Horne, C.L. Giles P.C. Collingwood, Finite State Machines and Recurrent Neural Networks --Automata and Dynamical Systems Approaches. Neural Networks and Pattern Recognition , (eds) J.E. Dayhoff, O. Omidvar, Academic Press, 171-220, 1998.
• G.Z.Sun, C.L. Giles, H.H. Chen, Y.C. Lee, The Neural Network Pushdown Automata: Architecture, Dynamics and Training, in  Adaptive Processing of Sequences and Data Structures, (eds) C.L. Giles, M. Gori, Lecture Notes in Artificial Intelligence, 296-345, Springer Verlag, 1998.
• M. Maggini, C.L. Giles, B.G. Horne, Financial Time Series Forecasting Using K-Nearest Neighbors Classification, Nonlinear Financial Forecasting, Proceedings of the First INFFC, (ed) R.B. Caldwell, p. 169, Finance & Technology Publishing Haymarket, VA, 1997.
• S. Lawrence, S. Fong, C.L. Giles Natural Language Grammatical Inference: A Comparison of Recurrent Neural Networks and Machine Learning Methods, Lecture Notes on Artificial Intelligence, Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing, eds. S. Wermter, E. Riloff, G. Scheler, Springer-Verlag, NY, 1996.
• D. Chen, C.L. Giles, G.Z. Sun, M. Goudreau, H.H. Chen, Y.C. Lee, “A Method for Constructive Learning of Recurrent Neural Networks,” Ch. 6, Computational Learning Theory and Natural Learning Systems III,” (eds) T. Petsche, S. Hanson, J. Shavlik, MIT Press, Cambridge, MA, 1995.
• H.T. Siegelmann, B.G. Horne, C.L. Giles, “What NARX Networks Can Compute,” Lecture Notes in Computer Science, (eds) M.Bartosek, J.Staudek, J.Wiedermann, vol. 1012, Springer-Verlag, NY, 1995.
• C.L. Giles, C.B. Miller, “The Effect of Higher Order in Recurrent Neural Networks: Experiments,” Ch 6, Artificial Neural Networks for Speech and Vision, (ed) R.J. Mammone, Chapman & Hall, London, 1994.
• M.W. Goudreau, C.L. Giles, “Routing in Random Multistage Interconnection Networks,” Ch 3, Neural Network Applications in Telecommunications, (eds) B. Yuhas, N. Ansari, Kluwer, Cambridge, MA, 1994.
• C.W. Omlin and C.L. Giles, “Extraction and Insertion of Symbolic Information in Recurrent Neural Networks,” in Artificial Intelligence and Neural Networks: Steps Toward Principled Integration, (eds) V. Honavar and L. Uhr, Academic Press, Cambridge, Chapter XII, MA, 1994.
• C.L. Giles, T. Maxwell, “Learning, Invariance, and Generalization in High Order Neural Networks,” Applied Optics, 26(23), p. 4972, 1987. Reprinted in: Selected Papers on Optical Neural Networks, (ed) S. Jutamulia, SPIE Milestone Series, vol. MS 96, 1994.
•  C.B. Miller, C.L. Giles, “Experimental Comparison of the Effect of Order in Recurrent Neural Networks,” International Journal of Pattern Recognition and Artificial Intelligence, 7(4), p. 849, 1993. Reprinted in: Advances in Pattern Recognition Systems Using Neural Network Technologies, (eds) I. Guyon, P.S.P. Wang, Series in Machine Perception & Artificial Intelligence - Vol 7, World Scientific, River Edge, N.J., 1993.
•  C.L. Giles, et.al., “Learning and Extracting Finite State Automata with Second-Order Recurrent Neural Networks,” Neural Computation, 4(3), p. 393, 1992. Reprinted in: Artificial Neural Networks, (eds) E. Sanchez-Sinencia, C. Lau, IEEE Press, Piscataway, N.J., 1992.
•  C.L. Giles, T. Maxwell, “Learning, Invariance, and Generalization in High Order Neural Networks,” Applied Optics, 26(23), p. 4972, 1987. Reprinted in: Artificial Neural Networks: Concepts and Theory, (eds) P. Mehra and B. W. Wah, IEEE Computer Society Press, Los Alamitos, CA., 1992.
 

Edited Proceedings and Special Issues:

• C.L. Giles, R. Sun, J. Zurada (Guest Editors) - Special Issue on “Neural Networks and Hybrid Intelligent Models: Foundations, Theory, and Applications,” IEEE Trans. on Neural Networks, 9(5), 1998.
• C.L. Giles, M. Gori, Adaptive Processing of Sequences and Data Structures, Lecture Notes in Artificial Intelligence, Springer -Verlag, 1998.
• J. Principe, L. Giles, N. Morgan, E. Wilson, Proceedings of the 1997 IEEE Workshop Neural Networks for Signal Processing VII, IEEE Press, 1997.
• C.L. Giles, G.M. Kuhn, R.J. Williams (Guest Editors) - Special Issue on “Dynamical Recurrent Neural Networks,” IEEE Trans. on Neural Networks, 5(2), 1994.
• S.J. Hanson, J.D. Cowan, C.L. Giles, Advances in Neural Information Processing Systems 5, Morgan Kaufmann, San Mateo, CA, 1993.
• B.K. Jenkins, S.H. Lee, C.L. Giles, Guest Editors, “Optical Computing”, Applied Optics, 31(26), 1992.

Letters to the Editor (refereed):

• C.L. Giles, S. Lawrence, B. Krovetz, “Access to Information on the Web,” Science, 280(5371), p. 1815, 1998.
• S. Lawrence, C.L. Giles, “Searching the Web,” Science, 281(5374), p. 175, 1998.

Technical Reports:

• Andrew D. Back, Ah Chung Tsoi, Bill G. Horne, C. Lee Giles, Alternative Discrete-Time Operators and Their Application to Nonlinear Models, U. of Maryland Technical Report CS-TR-3738 and UMIACS-TR-97-03, 1997.
• M.F. Sakr, S.P. Levitan, D.M. Chiarulli, B.G. Horne, C.L. Giles, Performance of On-Line Learning Methods in Predicting Multiprocessor Memory Access Patterns, U. of Maryland Technical Report UMIACS-TR-96-59 and CS-TR-3676, 1996.
• Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, What Size Neural Network Gives Optimal Generalization? Convergence Properties of Backpropagation. U. of Maryland Technical Report CS-TR-3617.
• Steve Lawrence, C. Lee Giles, Sandiway Fong, On the Applicability of Neural Network and Machine Learning Methodologies to Natural Language Processing. Technical Report UMIACS-TR-95-64.
• P. Tino, B.G. Horne, C.L. Giles, Fixed Points in Two--Neuron Discrete Time Recurrent Networks: Stability and Bifurcation Considerations."Technical Report UMIACS-TR-95-51.
• C.W. Omlin, C.L. Giles, Fault-Tolerant Implementation of Finite-State Automata in Recurrent Neural Networks.RPI Computer Science Technical Report 95-3.
• Daniel S. Clouse, C.L. Giles, B.G. Horne, G.W. Cottrell, Learning Large DeBruijn Automata with Feed-Forward Neural Networks. Technical Report UCSD CS94-398.

Copyright 2006  C. Lee Giles
All rights reserved.