Robert C. Williamson - Publications
May 23, 2005
All of my "publications" are listed below, even unpublished ones.
The numbers associated with each publication are a "serial number"
assigned in approximately chronological order. Since omission of
unpublished ones would leave gaps, and since a chronological ordering is
rather useful, I have left all of the entries
here. Names in italics denote coauthor who was a graduate
student at the time of writing the initial paper.
Theses
- Robert C. Williamson, Number Theoretic Transform
Convolver,
Bachelor of Engineering Thesis (Q.I.T. 1983).
-
Robert C. Williamson, Software Implementation of
Polynomial Transform based Convolution Algorithms, Master of
Engineering Science Thesis, (University of Queensland 1985).
-
Robert C. Williamson,
Probabilistic
Arithmetic,"
PhD Thesis, (University of Queensland 1989).
Edited Volumes
[P92] Peter L. Bartlett, Anthony Burkitt, and Robert C.
Williamson (Editors), Proceedings of the Seventh Australian
Conference on Neural Networks, Department of Engineering, ANU, April
1996. ISBN 0 7315 2429 2, 261 pages.
[P152] David Helmbold and Bob Williamson (Editors),
Computational Learning Theory: 14th Annual Conference on
Computational learning theory, COLT2001 and 5th European Conference on
Computational learning Theory, EuroCOLT2001, Amsterdam, Netherthelands,
Proceedings, Springer Lecture Notes in Artifical Intelligence (LNAI)
2111, Springer, Berlin, 2001, ISBN 3-540-42343-5. (629 pages)
Book Chapters
[P8]
Robert C. Williamson, "Interval Arithmetic and Probabilistic
Arithmetic," in
Contributions to Computer
Arithmetic and Self-Validating Numerical Methods, Edited by C.
Ullrich, pages 67-80,
J.C. Baltzer AG, Scientific Publishing Co., 1990.
[P107] Robert C. Williamson, Alex J.Smola and Bernhard
Schölkopf,
"Entropy Numbers, Operators, and Support Vector
Kernels", chapter in Advances in Kernel Methods - Support
Vector Learning, MIT Press, to appear, 1998.
[P120] Alex J.Smola, Andreé Elisseff, Bernhard Schölkopf
and Robert C. Williamson, "Entropy Numbers
for Convex Combinations and
MLPs," pages 369-387 in Alex Smola, Peter Bartlett,
Bernhard Schölkopf and Dale Schuurmans
(Editors), Advances in Large Margin Classifiers, MIT Press, 2000.
[P158] Ralf Herbrich and Robert C. Williamson,
Learning and Generalization: Theoretical
Bounds, invited
submission to Michael Arbib (Ed.) Handbook of Brain Theory and
Neural Networks, 2nd Edition, MIT Press, 2002. ISBN
0-262-01197-2
[P94]
Jennifer A. Fulton, Robert R. Bitmead and
Robert C. Williamson,
"Smoothing Approaches to Reconstruction of
Missing Data in Array
Processing,"
pages 87-94, in Defence Applications of Signal Processingi -
Proceedings of the US/Australia Joint Workshop on Defence Applications
of Signal Processing, Elsevier, 2001. (Work submitted in 1997!)
[P153] Darren B. Ward, Rodney A. Kennedy and Robert C. Williamson,
"Constant Directivity beamforming," pages 3-17 in Michael
Brandstein and Darren Ward (Eds) Microphone Arrays:
Signal Processing Techniques and Applications, Springer,
Berlin, 2001. ISBN 3-540-41953-5.
Book Chapters (Submitted)
[P138] Ralf Herbrich, Thore Graepel and Robert C. Williamson,
The Structure of Version
Space,
submitted to Book, Edited by Dawn Holmes and L.C. Jain, Springer,
January 2005. Also Microsoft Technical Report
MSR-TR-2004-63 July 2004.
Journal Papers
[P3]
Robert C. Williamson and Tom Downs, "The Inverse and
Determinant of a 2×2 Uniformly Distributed Random
Matrix," Statistics and Probability Letters ,
7, pages 167-170,
(1989).
[P5]
Robert C. Williamson and Tom Downs, "Probabilistic
Arithmetic: Numerical Methods for Calculating Convolutions
and Dependency Bounds," International
Journal of Approximate Reasoning 4, pages
89-158 (1990).
[P6]
Robert C. Williamson, "An Extreme Limit Theorem for
Dependency Bounds of Normalised Sums of Random Variables,"
Information Sciences , 56,
pages 113-141 (1991).
[P7]
Robert C. Williamson, "The Law of Large Numbers for Fuzzy
Variables under a General Triangular Norm Extension
Principle," Fuzzy Sets and Systems, 41,
55-81, (1991).
[P18]
Brian C. Lovell and Robert C. Williamson, The
Statistical Performance of Some Instantaneous Frequency
Estimators,,
IEEE Transactions on Signal Processing
40, pages 1708-1723,
(July 1992).
[P34]
Brian C. Lovell, Robert C. Williamson and Boaulem Boashash,
The Relationship Between Instantaneous Frequency
and Time Frequency
Representations,
IEEE Transactions on
Signal Processing , 41, pages 1458-1461 (1993).
[P44]
Robert C. Williamson, Ben James, Brian D.O. Anderson
and Peter J. Kootsookos, "Threshold
Effects in Maximum Likelihood Multiharmonic Frequency
Estimation,"
Signal Processing, 37, pages 309-331, (1994).
[P45]
Ben James, Brian D.O. Anderson, and Robert C. Williamson,
"Conditional Mean and Maximum Likelihood Approaches to
Multiharmonic Frequency Estimation," IEEE
Transactions on Signal Processing, 42, pages 1366-1375
(June 1994)
[P32]
Mehmet Karan, Brian D.O. Anderson and
Robert C. Williamson, "Performance of Maximum Likelihood
Estimator for Frequency Tracking Problems",
IEEE Transactions on Signal Processing, 42(10),
2749-2757, (1994) .
[P43]
Darren Ward,
Rodney A. Kennedy and Robert C. Williamson,
"The Theory of Broadband Sensor Arrays with Frequency Invariant Far-Field Beam Patterns"
Journal of the Acoustical Society of America 97(2),
1023-1034, (February 1995)
[P30]
Robert C. Williamson and Uwe Helmke, "Existence and
Uniqueness Results for Neural Network Approximations,"
IEEE Transactions on Neural Networks, 6(1), 2-13,
(1995)
[P31]
Ben James, Brian D.O. Anderson and Robert C. Williamson,
"Characterization of Threshold for Single Tone Maximum
Likelihood Estimation," IEEE Transactions on
Signal Processing 43(4), 817-821, (April 1995)
[P56]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"Lower Bounds on the VC-Dimension of
Smoothly Parametrized
Function Classes",
Neural Computation
7(5), 1040-1053 (1995) (N.B. theorem 10 in this paper is wrong;
A correction has been accepted for publication which
rescues the result on neural networks.)
[P33]
Uwe Helmke and Robert C. Williamson,
"Neural Networks,
Rational Functions and Realization
Theory"
Mathematics of Control, Signals and
Systems,
8(1), 27-50, (1995).
[P54]
Mehmet Karan, Brian D.O. Anderson and Robert C. Williamson,
"Efficient Calculation of the Moments of Matched and Mismatched
Hidden Markov
Models," IEEE Transactions on Signal
Processing, 43(10), 2422-2425, (1995)
[P41]
Kim L. Blackmore, Iven M.Y. Mareels, and Robert C.
Williamson, "Learning Nonlinearly Parametrized
Decision
Regions"
Summary in Journal of Mathematical Systems,
Estimation and Control , 6(1), 129-132 (1996).
Full version to appear later, and available electronically from
ftp://ftp.birkhauser.com/journals/jmsec/articles/gzip/88289.ps.gz .
[P55]
Peter J. Kootsookos and Robert C. Williamson, "FIR Approximation
of Fractional Sample Delay Systems" IEEE
Transactions on Circuits and Systems II: Analog and Digital Signal
Processing 43(3), 269-271 (1996)
[P46]
Peter L. Bartlett and Robert C. Williamson,
"The VC-Dimension and
Pseudodimension of Two-Layer Neural networks with Discrete
Inputs,"
Neural Computation 8, 653-656 (1996).
[P61]
Darren B. Ward, Rodney A. Kennedy and Robert C. Williamson,
"FIR Filter Design for Frequency Invariant
Beamformers,"
IEEE Signal Processing Letters, 3, pages 69-71, March
1996.
[P42]
Kim L. Blackmore, Robert C. Williamson and
Iven M.Y. Mareels, "Local Minima and
Attractors at Infinity of Gradient Descent Learning
Algorithms,"
Summary in Journal of Mathematical Systems, Estimation and
Control, 6(2), pages 231-234, (1996).
Full version to appear later, and available electronically from
ftp://trick.nte.springer.de/jmsec/85167.ps.
[P53]
Peter L. Bartlett, Philip M. Long and Robert C.
Williamson,
"Fat-Shattering and the Learnability of
Real-Valued
Functions"
Journal of Computer and System Sciences, 52(3),
434-452, (1996).
[P57]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"Efficient Agnostic Learning of Neural
Networks with Bounded
Fan-in"
IEEE Transactions on Information Theory, 42(6),
2118-2132, (1996).
[P64]
Jennifer Fulton, Robert R. Bitmead, and Robert C.
Williamson, "Sampling versus Quantization in Speech Coders",
Signal Processing 56(3), 209-218, 1997.
[P59]
Kim L. Blackmore, Robert C. Williamson and
Iven M.Y. Mareels, "Decision Region
Approximation",
IEEE Transactions on Information Theory, 43(3),
903-907, 1997.
[P63]
Kim L. Blackmore, Robert C. Williamson, Iven M.Y. Mareels,
William A. Sethares, "On-line Learning via
Congregational Gradient
Descent",
Mathematics of Control, Signals and Systems,
10(4), 331-363, 1997.
[P97] Darren B. Ward, Robert C. Williamson and Rodney A. Kennedy,
"Broadband Microphone Arrays for Speech
Acquisition,"
in Acoustics Australia, 26(1), 17-20, April 1998.
[P65]
Erik Weyer, Iven M.Y. Mareels and Robert C. Williamson,
"On the Relationship Between Behavioural and Standard Methods for
System Identification", Automatica 34(6), 801-804,
1998.
[P77]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"The Importance of Convexity in Learning with
Squared
Loss"
IEEE Transactions on Information Theory 44(5),
1974-1980, 1998.
[P85]
John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson and
Martin Anthony,
"Structural Risk Minimization over
Data-Dependent
Hierarchies",
IEEE Transactions on Information Theory, 44(5),
1926-1940 (1998).
[P88]
Peter J. Kootsookos, Darren B. Ward, and
Robert C. Williamson,
"Imposing Pattern nulls on broadband array
responses,"
Journal of the Acoustical Society of
America, 105(6), 3390-3398, June 1999.
(Expanded journal version of P74.)
[P117] Thushara D. Abhayapala, Rodney A. Kennedy and
Robert C. Williamson,
"Spatial Aliasing for Nearfield Sensor Arrays," Electronics Letters,
35(10), 764-765, 13 May 1999.
[P78] Erik Weyer, Iven M.Y. Mareels, and
Robert C. Williamson,
"Sample Complexity of Stochastic
Least Squares System Identification",
IEEE Transactions on
Automatic Control, 44(7), 1370-1383 (1999)
(submitted 1995 and actually based in part on results in a CDC
paper from 1992!)
[P108] Thushara D. Abhayapala, Rodney A. Kennedy and
Robert C. Williamson, "Noise Modelling for Nearfield Array gain Optimization," IEEE Signal
Processing Letters,6(8), 210-212, August 1999.
[P93]
Thushara Abhayapala, Rodney A. Kennedy and
Robert C. Williamson,
"Nearfield broadband array design
using a radially invariant modal
expansion",
Journal of the Acoustical
Society of America, 107(1), 392-403, 2000.
[P101] Biljana Radlovi\'c, Robert C. Williamson and
Rodney A. Kennedy, "Equalization in an Acoustic
Reverberant Environment: Robustness
Results,"
IEEE Transactions on Speech and Audio Processing, 8(3),
311-319, May 2000.
[P115] Bernhard Schölkopf, Alex Smola, Robert Williamson and
Peter Bartlett, "New Support Vector
Algorithms,"
Neural Computation 12(5), 1207-1245, May 2000.
[P116] Alex J. Smola, Sebastian Mika, Bernhard Schölkopf and
Robert C. Williamson, "Regularised Principal
Manifolds",
Journal of Machine Learning Research, 1, 179-209, 2001.
[P128] Simon I. Hill and Robert C. Williamson,
"Convergence of Exponentiated Gradient
Algorithms,"
IEEE Transactions on
Signal Procesing, 49(6), 1208-1215, June 2001.
[P132] Bernhard Schölkopf, John C. Platt, John Shawe-Taylor,
Robert C. Williamson and Alex J.Smola, "Estimating
the Support of a High-Dimensional
Distribution,",
Microssoft technical report MSR-TR-99-87.
Slightly abridged version in
Neural Computation 13(7), 1443-1471, 2001.
[Full version of P126].
[P102]
Robert E. Mahony and Robert C. Williamson, "Prior
Knowledge and Preferential Structures in Learning
Algorithms,"
Journal of Machine Learning Research, 1, 311-355, 2001. (see
the final version on the JMLR web page
[P100] Robert C. Williamson, Alex Smola and Bernhard
Schölkpof, "Generalization Performance
of Regularization Networks and Support Vector Machines via
Entropy Numbers of Compact
Operators,"
IEEE Transactions on Information Theory, 47(6), 2516-2532,
2001.
[P133]
Ying Guo, Peter L. Bartlett, John
Shawe-Taylor and Robert C. Williamson,
"Covering Numbers for Support Vector
Machines",
IEEE Transactions on Information Theory 48(1), 239-250,
January 2002.
[Refined version of P118]
[P159] Ralf
Herbrich
and Robert C. Williamson,
"Algorithmic
Luckiness"
Journal of Machine
Learning Research 3, 175-212 (2002).
[P172] Jyrki Kivinen, Alexander J. Smola and Robert C. Williamson,
Online Learning With
Kernels,
IEEE Transactions on Signal Processing, 52(8), 2165-2176,
August 2004.
[P142] Richard K. Martin, William A. Sethares, and Robert C.
Williamson, "Exploiting Sparsity in
Adaptive
Filters,"
IEEE transactions on Signal Processing, 50(8), 1883-1893,
August 2002.
[P168] Darren B. Ward, Eric A. Lehmann and Robert C.
WIlliamson, Particle Filtering Algorithms for Tracking
an Acoustic Source in a Reverberant
Environment,
IEEE Transactions on Speech
and Audio Processing, 11(6), 826-836, November 2003.
Accepted Journal Papers
[P129] Robert C. Williamson, John Shawe-Taylor, Bernhard
Schölkopf and Alex J. Smola, "Sample Based
Generalization
Bounds,"
accepted subject to revision to
IEEE Transactions on Information Theory,
November 1999.
Submitted Journal Papers
[P89]
D.B. Ward, R.A. Kennedy, and R.C. Williamson, "Adaptive
broadband beamforming with a frequency invariant beampattern
parameterization," Intern. Journal of Adapt. Control and
Signal Process., (submitted March 1997).
[P147] Ying Guo, Peter Bartlett, Alex J. Smola, Robert C.
Williamson and Jonathan Baxter, "Norm-based
Regularization of
Boosting,"
submitted to Journal of Machine Learning Research, August 2001.
[P171] Cheng Soon Ong, Alexander J. Smola and Robert C.
Williamson, "Learning the Kernel with
Hyperkernels,",
submitted to Journal of Machine Learning Research, May 2003.
[P173] Eric A. Lehmann and Robert C. Williamson,
"Particle Filter Design using Importance Sampling for
Acoustic Source Localisation and Tracking in Reverberant Environments," submitted to
EURASIP Journal on Applied Signal Processing,
special issue on Advances in Multi-Microphone Speech Processing. January
2005.
[P175] Adam Kowalczyk, Alex J. Smola and Robert C. Williamson,
"Logic, Trees and
Kernels, submitted to
Journal of Machine Learning Research, 2003.
Patents
[P141] William A. Sethares, Richard K. Martin and Robert C.
Williamson, "New Adaptive methods that Exploit Sparsity,"
preliminary patent disclosure, 9 pages. July 2000.
Refereed Conference Papers (International)
[P2]
R.C. Williamson and T. Downs, "Probabilistic Arithmetic and
the Distribution of Functions of Random Variables,"
Proceedings of the 1987 IASTED
International Symposium on Signal Processing and its
Applications , 112-119, Brisbane, (1987)
[P1]
R.C. Williamson and L.C. Westphal, "Efficient Software
Implementation of Cyclic Convolution Algorithms Based on
Polynomial Transforms," IREECON
International Digest of Papers , 579-582, Melbourne, (1985)
[P4]
Robert C. Williamson, "Interval Arithmetic and Probabilistic
Arithmetic," IMACS-GAMM-GI International Symposium on
Computer Arithmetic and Self-Validating Numerical Methods,
Basel, (4 pages, no page numbers) (October 1989)
[P9]
Brian C. Lovell, Peter J. Kootsookos and Robert C. Williamson,
"Efficient Frequency Estimation and Time-Frequency
Representations," Proceedings of the International
Symposium on Signal Processing and its Applications (ISSPA90),
170-173, (August 1990)
[P11]
Robert C. Williamson, "e-Entropy and the
Complexity of Feedforward Neural Networks,"
Neural Information Processing Systems 3,
pages 946-952, Morgan Kaufmann, San Mateo, (April 1991)
[P10]
Mark J. Damborg, Robert C. Williamson, Andrew D.B.
Paice and
John B. Moore, "Adaptive Nonlinear Estimation with Artificial
Neural Networks," Proceedings of International
Symposium on
Information Theory and its Applications (ISSITA), pages
743-746 (1990)
[P12]
Brian C. Lovell, Peter J. Kootsookos and Robert C. Williamson,
"The Circular Nature of Discrete-time Frequency
Estimates,"
Proceedings of International Conference on
Acoustics, Speech and Signal
Processing,
pages 3369-3372, (May 1991)
[P13]
Peter L. Bartlett and Robert C. Williamson, "Perceptron
Learning with Reasonable Distributions of Training Examples,"
Proceedings of the International Conference
on Artificial Neural Networks, Volume 2, pages 1033-1036,
(1991)
[P14]
Robert C. Williamson and William A. Sethares, "A Provably
Convergent Perceptron-like Algorithm for Learning Hyper-cubic
Decision Regions," Proceedings of the
International Conference on Artificial Neural Networks,
Volume 2, pages 1029-1032, (1991)
[P15]
Peter L. Bartlett and Robert C. Williamson, "Investigating the
Distribution Assumptions in the PAC Learning Model,"
Proceedings of the Workshop on Computational Learning
Theory, Morgan Kauffmann, San Mateo, pages 24-32, (1991)
[P19]
Ben James, Brian D.O. Anderson, and Robert C. Williamson,
"Characterization of Threshold for Multiharmonic Maximum
Likelihood Frequency Estimation," Proceedings of
the International Symposium on Signal Processing and
Applications, pages 255-258, (1992)
[P20]
Robert C. Williamson and Peter L. Bartlett, "Splines,
Rational Functions, and Neural Networks,"
Advances in Neural
Information Processing Systems 4, Morgan Kaufmann, San Mateo,
pages 1040-1047,
(1992)
[P21]
Erik Weyer, Robert C. Williamson and Iven M.Y. Mareels,
"An Approach to System Identification Based on Risk
Minimization and Behaviours", Proceedings of the
31st Conference on Decision and Control, pages 927-932, (1992)
[P35]
Erik Weyer, Robert C. Williamson, and Iven M.Y. Mareels,
"A Principle for System Identification in the Behavioural Framework"
Proceedings of the 12th World Congress of the International
Federation of Automatic Control, Volume 7, pages 387-390 (July
1993)
[P36]
Kim L. Halliwell, Robert C. Williamson, and Iven M.Y. Mareels,
"Learning Nonlinearly Parametrized Decision Regions"
Proceedings of the 12th World Congress of the International
Federation of Automatic Control, Volume 5, pages 431-434
(July 1993)
[P37]
Uwe Helmke and Robert C. Williamson "Rational Parametrizations
of Neural Networks," Neural Information
Processing Systems - 5, Morgan Kaufmann, San Mateo, pages
623-630, (1993).
[P38]
Mehmet Karan, Brian D.O. Anderson and Robert C. Williamson,
"A Note on the Calculation of the Kullback-Leibler Number
between
Hidden Markov Models", Proceedings of the Second
International Workshop on Intelligent
Signal Processing and Communication Systems, Japan,
pages 93-98, (October 1993)
[P39]
Mehmet Karan, Brian D.O. Anderson and Robert C. Williamson,
"Robustness of Maximum-Likelihood Frequency Estimators Under Model
Errors", Proceedings of IEEE Conference on Decision and
Control, pages 3034-3039, (December 1993)
[P80]
Uwe Helmke and Robert C. Williamson, "Parametrization Aspects of
Neural Networks and Linear System Theory," Proceedings of the
European Control Conference, Groningen, 1993.
[P47]
Mehmet Karan, Brian D.O. Anderson and Robert C. Williamson,
"A Simple Calculation of the Joint Moments of Hidden Markov
Models," Proceedings of International Conference on Acoustics,
Speech and Signal Processing, pages IV-333-IV-335, (May 1994)
[P48]
Darren Ward, Rodney A. Kennedy and Robert C. Williamson,
"Design of Frequency-Invariant Broadband Far-field Sensor
Arrays," pages 1274-1277 of volume 2 of Proceedings of the
IEEE Antennas and Propagation Society
International Symposium and URSI Radio Science Meeting (July
1994). ISBN 0-7803-2009-3.
[P49]
Peter L. Bartlett, Philip M. Long and Robert C. Williamson,
"Fat-shattering and the learnability of real-valued functions",
Proceedings of the Seventh
Annual ACM Conference on Computational Learning Theory,
pages 299-310,
(July 1994)
[P50]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"Lower Bounds on the VC-Dimension of Smoothly Parametrized
Function Classes", Proceedings of the Seventh
Annual ACM Conference on Computational Learning Theory,
pages 362-367,
(July 1994)
[P67]
Kim L. Blackmore, Robert C. Williamson, Iven M.Y. Mareels,
William A. Sethares, "On-line Learning via
Congregational Gradient Descent" pages 265-272 in Proceedings of
the Eighth Annual ACM Conference on Computational Learning
Theory (1995).
[P68]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"On Efficient Agnostic Learning of
Linear Combinations of Basis
Functions"
pages 369-376 in Proceedings of the Eighth Annual
ACM Conference on Computational Learning Theory (1995).
[P69]
Darren B. Ward, Rodney A. Kennedy and Robert C. Williamson,
"Broadband Beamforming with a Single Set of Filter Coefficients"
in Proceedings of the 1995 IEEE
Singapore Int. Conf. on Signal Processing, Circuits and Systems,
pp88-93, Singapore, July 1995.
[P71]
A. Kowalczyk, J. Szymanski, and R.C. Williamson,
"Learning Curves from a Modified VC-Formalism: a Case Study,",
Proceedings of IEEE International Conference on Neural
Networks (ICNN'95), Volume 6, pp2939-2943.
[P81]
John Shawe-Taylor, Peter Bartlett, Robert C. Williamson,
Martin Anthony, "A Framework for Structural Risk Minimisation"
Proceedings of the 9th Annual Conference on
Computational Learning Theory, pages 68-76, 1996.
[P82]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"The Importance of Convexity in Learning with Squared Loss"
Proceedings of the 9th Annual Conference on
Computational Learning Theory, pages 140-146, 1996.
[P70]
A. Kowalczyk, J. Szymanski, P.L. Bartlett and R.C. Williamson,
"Examples of Learning Curves from a Modified VC-Formalism,"
Advances in Neural Information Processing Systems 8, MIT
Press, 1996 (ISBN 0-262-20107-0).
[P74]
Peter J. Kootsookos, Darren B. Ward, and Robert C.
Williamson, "Frequency Invariant Broadband Beamforming with Exact
Null Design", pages 105-108 in Proceedings of the 8th IEEE
signal Processing Workshop on Statistical Signal and Array
Processing, 1996. ISBN 0-8186-7576-4.
[P75]
Rodney A. Kennedy, Thushara Abhayapala, Darren B. Ward,
and Robert C. Williamson, "Nearfield Broadband Frequency
Invariant Beamforming", pages 905-908 of volume 2 of
Proceedings of
IEEE Conference on Acoustics, Speech and Signal
Processing, 1996.
[P72]
Erik Weyer, Iven M.Y. Mareels and Robert C. Williamson,
"Behavioural Oriented Identification in a Stochastic
Framework," Proceedings of the 13th
IFAC World Congress 1996. Volume I, pages 1-6.
ISBN 0-08-042605-0 (CDROM); 0-08-042908-4 (paper).
[P73]
Erik Weyer, Iven M.Y. Mareels and Robert C. Williamson,
"Sample Complexity of Least Squares Identification of FIR and
ARX Models," Proceedings of the 13th
IFAC World Congress 1996. Volume J, pages 239-244.
ISBN 0-08-042605-0 (CDROM); 0-08-042908-4 (paper).
[P83]
Kim L. Blackmore, Robert C. Williamson, and
Iven M.Y. Mareels, "Hasty Congregational Gradient Descent for
Online Optimisation,"
in the Proceedings of the Australian Engineering
Mathematics Conference 1996 (An International Conference on
Engineering Mathematics: Research, Education and Industry
Linkage), 15-17 July 1996.
[P90] John Shawe-Taylor and Robert C. Williamson,
"A PAC Analysis of a Bayesian Estimator",
Proceedings of the Tenth Annual Conference on Computational
Learning Theory (COLT97), pages 2-9, July 1997.
(Published by the Association for Computing Machinery, New York.
ISBN 0-89791-891-6)
[P84]
Darren B. Ward, Rodney A. Kennedy and Robert C.
Williamson, "An Adaptive Algorithm for Broadband Frequency
Invariant Beamforming,"
Proceedings of the IEEE Conference on
Acoustics, Speech and Signal Processing, April 1997.
[P96]
Robert C. Williamson, "Some Results in
Statistical Learning Theory with Relevance to Nonlinear
System Identification," IFAC Nonlinear Control
Systems Design Symposium
1998 (NOLCOS98), Preprints, Volume 2, pages 443-448.
To appear in the proceedings
published by Elsevier
[P95]
Thushara D. Abhayapala, Rodney A. Kenedy and
Robert C. Williamson, "Broadband Beamforming Using Elementary
Shape Invariant Beampatterns," Proceedings of ICASSP'98,
volume 4, pages 2041-2044.
[P98]
Bernhard Schölkopf, Peter L. Bartlett, Alex Smola and
Robert C. Williamson,
"Support Vector Regression with Automatic
Accuracy Control",
In L. Niklasson and M. Boden and
T. Ziemke (eds.). Proceedings of the 8th International Conference
on Artificial Neural Networks, pp. 111 - 116, Springer Verlag,
Perspectives in Neural Computing, Berlin.
[P106]
Thushara D. Abhayapala, Rodney A. Kennedy
and Robert C. Williamson, Farfield Array Weight Redesign for
Nearfield Beamforming, Proceedings of 6th IEEE Int. Workshop
on Intelligent Sig. Proc. and Comm. Syst. (ISPACS'98),
Volume 2, pp.537-540.
[P103]
Robert C. Williamson, Alex J. Smola and Bernhard Schölkopf,
"Entropy Numbers, Operators and Support Vector Kernels,"
Proceedings of the 4th European Conference on
Computational Learning Theory (EUROCOLT'99), 285-300, (1999).
[P112]
John Shawe-Taylor and Robert C. Williamson,
"Generalization Performance of Classifiers in Terms of Observed
Covering Numbers," Proceedings of
the 4th European Conference on
Computational Learning Theory (EUROCOLT'99), 274-284, (1999).
[P114]
Alex J. Smola, Robert C. Williamson, Sebastian Mika and Bernhard
Schölkopf,
"Regularized Principal
Manifolds,"
Proceedings of the 4th European Conference on
Computational Learning Theory (EUROCOLT'99) 214-229, (1999)
[P111]
Thushara D. Abhayapala, Rodney A. Kennedy and
Robert C. Williamson, "Isotropic Noise
Modelling for Nearfield Array
Processing,"
Proceedings of the IEEE Workshop on Applications of Signal
Processing to Audio and Acoustics (WASSPA99), pages
873 -876, vol.2 1999.
[P118]
Ying Guo, Peter L. Bartlett, John
Shawe-Taylor and Robert C. Williamson,
"Covering Numbers for Support Vector Machines", Proceedings of
the Twelfth Annual Conference on Computational Learning Theory,
pages 267-277, 1999.
[P121]
Simon Hill and Robert C. Williamson,
"A Signal Processing Analysis of the Exponentiated Gradient Descent Algorithm," Pages 379-382 in volume 1 of Proceedings of the Fifth
International Sympoisium on Signal Processing and its Applications,
(ISBN 1 86435 451 8) ISSPA99.
[P124]
Thushara D. Abhayapala, Rodney A. Kennedy,
Robert C. Williamson, and Darren B. Ward,
"Nearfield Broadband
Adaptive Beamforming,"
Pages 839-842,
volume 2 of Proceedings of the Fifth
International Sympoisium on Signal Processing and its Applications,
(ISBN 1 86435 451 8) ISSPA99.
[P125]
Darren B. Ward and Robert C. Williamson,
"Beamforming for a Source Located in
the Interior Field of an
Array,"
Pages 873-876 in
volume 2 of Proceedings of the Fifth
International Sympoisium on Signal Processing and its Applications,
(ISBN 1 86435 451 8) ISSPA99.
[P105]
Bernhard Schölkopf, Alex J. Smola, Peter L. Bartlett and
Robert C. Williamson, Shrinking the Tube:
A new Support Vector Regression
Algorithm,
to appear in M. S. Kearns, S. A. Solla,
and D. A. Cohn, editors, Advances in Neural Information
Processing Systems 11, MIT Press, Cambridge, MA.
[P130] Paul D. Teal, Robert C. Williamson and Rodney A. Kennedy,
"Error Performance of a Channel of Known Impulse
Response",
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00.
Proceedings. 2000 IEEE International Conference on ,
Volume: 5 , 2000 Page(s): 2733 -2736.
[P143] Marshall Shephard and Robert C. Williamson, "Very Low
Voltage Power Conversion,"
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International
Symposium on , Volume: 2 , 2001 Pages 289 -292 vol. 2.
[P123]
Bernhard Schölkopf, John Shawe-Taylor, Alex Smola and
Robert C. Williamson, "Kernel-Dependent Support Vector Error
Bounds,"
Artificial Neural Networks, 1999. ICANN 99.
Ninth International Conference on (Conf. Publ. No. 470) ,
Volume: 1 , 1999
[P110]
Biljana D. Radlovic, Robert C. Williamson and
Rodney A. Kennedy, "On the Poor Robustness of Sound Equalization in
Reverberant Environments,"
Acoustics, Speech, and Signal Processing, 1999. Proceedings.,
1999 IEEE International Conference on , Volume: 2 , 1999
Page(s): 881 -884 vol.2
[P134] Robert E. Mahony and Robert C. Williamson,
Riemannian Structure of Some New Gradient Descent
Learning
Algorithms
in Proceedings of the IEEE 2000 Adaptive
Systems for Signal Processing, Communication and Control Symposium
(AS-SPCC)), S. Haykin and J.
Principe
(Eds), IEEE Press, New Jersey, ISBN 0-7803-5800-7, pages 197-202.
[P127]
Alex Smola, John Shawe-Taylor, Bernhard Schölkopf and
Robert C. Williamson,
"The Entropy Regularization Information
Criterion,"
Advances in Neural Information processing Systems 12, (NIPS'99),
pages 342-348, MIT Press, 2000.
[P135] Robert C. Williamson, Alex J. Smola and Bernhard
Schölkopf, Entropy Numbers of Linear Function
Classes
Proceedings of COLT2000, 309-319, July 2000.
[P126]
Bernhard Schölkopf, Robert C. Williamson, Alex Smola,
John Shawe-Taylor and John Platt, "Support
Vector Method for Novelty
Detection,"
Advances in Neural Information processing Systems 12, (NIPS'99),
pages 582-588, MIT Press, 2000.
[P137] Alex J.Smola, Zoltán Óvári and Robert C.
Williamson, Regularization with Dot Product
Kernels,
Advances in neural Information processing Systems 13, (NIPS 2000),
pages 308-314, 2001.
[P140] Thore Graepel, Ralf Herbrich and Robert Williamson,
From Margin to
Sparsity,
Advances in neural Information processing Systems 13, (NIPS 2000),
pages 210-216, 2001.
[P155] Ralf
Herbrich
and Robert C. Williamson, "Algorithmic
Luckiness",
Advances in Neural Information processing Systems 14, T. G.
Dietterich, S. Becker and Z. Ghahramani (eds), MIT Press, 2002.
[P157] Darren B. Ward and Robert C. Williamson,
Particle Filtering Beamformingfor Acoustic Source
Localization in a Reveberant
Environment,
IEEE International Conference on Acoustics, Speech, and Signal
Processing (ICASSP-2002), vol. II, pp.1777-1780, Orlando, FL,
USA, May 2002.
[P91]
Shahar Mendelson and Robert C. Williamson,
"Agnostic Learning Nonconvex Function
Classes",
pages 1-13, in J. Kivinen and R.H. Sloan (Eds),
Computational Learning Theory
15th Annual Conference on Computational Learning Theory,
COLT 2002, Sydney, Australia, July 8-10, 2002. Proceedings
Lecture Notes in Artificial Intelligence 2375.
[P164] Eric A. Lehmann, Darren B. Ward and Robert C.
Williamson, Experimental Comparison of Particle
Filtering Algorithms for Acoustic Source Localization in a Reverberant
Room,
ICASSP 2003, vol. 5, pp. 177-180, Hong Kong, China, April 2003
[P149] Jyrki Kivinen, Alex Smola, and
Robert C. Williamson, "Online Learning with kernels",
in NIPS2001.
[P148] Adam Kowalczyk, Alex Smola and Robert C. Williamson,
"Kernel machines and Boolean functions" in NIPS2001.
[P162] Jyrki Kivinen, Alex Smola and Robert C. Williamson,
Large Margin Classification for Moving
Targets, ALT'02
(13th International Conference on Algorithmic Learning Theory), pages 113-127, Lecture Notes in Artificial Intelligence 2533,November
24-26, 2002.
[P122]
Thore Graepel, Ralf Herbrich, Bernhard Schölkopf,
Alex Smola, Peter Bartlett, Klaus-Robert Müller,
Klaus Obermayer and Robert Williamson,
"Classification on
Proximity Data with
LP-Machines," Ninth International Conference on Artificial Neural Networks, pages 304-309, London 1999.
Refereed Conference Papers (International) (Accepted)
[P150] Richard K. Martin, William A. Sethares, Robert C.
Williamson and C. Richard Johnson Jr, Exploiting
Sparsity in Adaptive
Filters, to appear in
Proceedings of 2001 Conference on Information Sciences and Systems, The
Johns Hopkins University, March 2001.
[P160] Cheng Soon Ong, Alex Smola and Robert C. Williamson,
Superkernels,
to appear in NIPS 2002.
[P161] Edward Harrington, Jyrki Kivinen,
Robert C. Williamson,
Ralf Herbrich and John Platt, Online Bayes
Point Machines,
to appear in PAKDD 2003.
[P165] Edward Harrington, Jyrki Kivinen and Robert C.
Williamson, Channel Equalization and the Bayes Point
Machine, to appear
in ICASSP 2003.
[P166] Terence Betlehem and Robert C.
Williamson,
Acoustic Beamforming Exploiting Directionality of Human Speech
Sources,
to appear in ICASSP 2003.
[P169]
James A. McGowan and Robert C. Williamson,
Loop Removal from LDPC
Codes,
to appear in Proceedings of the IEEE Information Theory Workshop,
Paris, Spring 2003.
Refereed Conference Papers (International) (Submitted)
[P146] Ying Guo, Peter L. Bartlett, Alex Smola and
Robert C. Williamson, "Norm based Regularization of Boosting"
submitted to NIPS2001.
[P174] Krzysztof Krakowski, Robert Mahony, Robert Williamson and
Manfred Warmuth, Online Learning on
Spheres submitted to
COLT2005, January 2005.
[P176] Omri Guttman, S.V.N. Vishwanathan and Robert C.
Williamson Learnability of Probabilistic Automata
via Oracles submitted to ALT2005.
Refereed Conference Papers (National)
[P16]
Robert C. Williamson and William A. Sethares, "Learning
Hyper-Cubic and Convex Polyhedral Decsion Regions Using
Perceptron-Like Algorithms" Proceedings of
the Second Australian Conference on Neural Networks ,
pages 126-129, (February 1991)
[P17]
Robert C. Williamson, "e-Entropy, Functional
Representation and Feedforward Neural Networks",
Proceedings of the Second Australian Conference on Neural
Networks , pages 155-158, (February 1991)
[P22]
Robert C. Williamson and Uwe Helmke, "Approximation Theoretic
Results for Neural Networks" Proceedings of the
Australian Conference on Neural Networks, pages 217-222,
(1992)
[P23]
Robert C. Williamson and Peter L. Bartlett, "Piecewise Linear
Feedforward Neural Networks," Proceedings of the
Australian Conference on Neural Networks, pages 260-261,
(1992)
[P40]
Kim Halliwell, Iven M.Y. Mareels, and Robert C. Williamson,
"Learning of Nonlinearly Parametrized Decision Regions,"
Proceedings of the Australian Conference on Neural Networks,
pages 74-77, (1993)
[P51]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"The Vapnik-Chervonenkis Dimension of Neural Networks with
Restricted Parameter Ranges", Proceedings of
Australian Conference on Neural Networks, pages 198-201, (1994)
[P52]
Kim L. Halliwell, Robert C. Williamson and Iven M.Y. Mareels,
"Local Minima and Attractors at Infinity of Gradient Descent
Learning Algorithms," Proceedings of
Australian Conference on Neural Networks, pages 161-164, (1994)
[P58]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"Efficient Agnostic Learning of Neural Networks with Bounded
Fan-in" Proceedings of
Australian Conference on Neural Networks, pages 201-204,
1995
[P66]
Kim L. Blackmore, Robert C. Williamson and Iven M.Y.
Mareels, "Decision Region Approximation" Proceedings of
Australian Conference on Neural Networks, pages 106-109, 1995
[P90]
Kim L. Blackmore, Robert C. Williamson and Iven M.Y.
Mareels, "Decision Region Approximation" (abstract only)
Proceedings of the Australian and New Zealand Industrial
and Applied Mathematics Conference.
[P60]
Peter L. Bartlett and Robert C. Williamson,
"The sample complexity of neural network learning with
discrete inputs" Proceedings of Australian Conference on Neural
Networks, pages 189-192, 1995
[P167]
James A. McGowan and Robert C. Williamson,
Removing Loops for LDPC
Codes,
to appear in Proceedings of Australian Communications Theory Workshop
2003.
Tutorials
Reviews
[P163] Robert C. Williamson, Review of Learning Kernel
Classifiers, Neural Networks 15, p.930, 2002.
Talks
[P136] Robert C. Williamson
`Margins, Sparsity and
Perceptrons',
talk presented an Neural Networks 2000 (Workshop held in Graz,
Austria, May 2000).
[P144] Robert C. Williamson,
"Telephones," special invited
lecture for ENGN1211 Discovering Engineering on the history
of the telephone.
[P145] Robert C. Williamson, "Riemannian
Structure of Some New Gradient Descent Learning
Algorithms",
talk given at ANU, 21/9/2000.
[P151] Robert C. Williamson,
"SRM and VC Theory", talk
presented at Dagstuhl
on Inference Principles and Model Selection.
[P154] Robert C. Williamson, Incorporating
Priors in Classical Gradient Descent Learning
Algorithms talk
given at Microsoft
Research (Cambridge and Redmond),
July/August 2001
[P156] Robert C. Williamson,
"Inductive
Principles," Talk
presented at the Machine Learning Summer School. Canberra, February, 2002.
[P170] Robert C. Williamson, "Machine
Learning - A Personal
Introduction,
presented at the Machine Learning Summer School, Canberra, February
2003.
Workshops (with proceedings)
[P24]
Brian D.O. Anderson, Ben James and Robert C.
Williamson,
"Frequency Line Tracking, Extended Kalman Filters and Some
HMM Problems," Proceedings of the Wirrina Cove HMM
Workshop, (11 pages, no page numbers), (1992).
Technical Reports
Unpublished Reports
[P79]
Peter L. Bartlett and Robert C. Williamson,
"Sample Complexity versus Approximation
Error" (1993)
[P76]
Jennifer A. Fulton, Robert R. Bitmead and Robert C.
Williamson, "Sampling Below the Nyquist Rate in an ADPCM
Speech Coder," submitted to IEEE Conference on Acoustics,
Speech and Signal Processing, 1996. (not accepted)
[P26]
Ben James, Brian D.O. Anderson and Robert C. Williamson,
"Characterization of Threshold for Multiharmonic Maximum
Likelihood Estimation," submitted to IEEE Transactions on
Signal Processing.
[P25]
Robert C. Williamson and Andrew D.B. Paice, "The Number of
Nodes Required in a Feed-Forward Neural Network for Functional
Representation," submitted to Neural Networks (under
revision 1990). I never bothered to resubmit in the end; the
work was effectively superseded by results published by Barron
in 1992. It was an extended version of P11.
[P27]
Ben James, Brian D.O. Anderson and Robert C. Williamson,
"Multiharmonic Frequency Estimation in Noise," submitted to
Signal Processing. I believe this was rejected, but I can
not find the letter...
[P28]
Erik Weyer, Robert C. Williamson and Iven M.Y. Mareels,
"System Identification in the Behavioural Framework. Part I:
Philosophy", submitted
to Automatica, (under revision 1993)
[P29]
Erik Weyer, Robert C. Williamson and Iven M.Y. Mareels,
"System Identification in the Behavioural Framework. Part II:
Analysis", submitted
to Automatica, (under revision 1993)
Automatica didn't like this and it has along with
P28 since evolved into other papers: P65, P73, P78.
[P62]
Wee Sun Lee, Peter L. Bartlett and Robert C. Williamson,
"On Efficient Agnostic Learning of Linear Combinations of Basis
Functions", submitted to Information and Computation 1994.
For reasons which to us which were very odd, this journal did not
like this paper. As a number of the results appeared in the
conference proceedings [P68] (albeit without some proofs), we
have not resubmitted it.
[P86]
Kim L. Blackmore, Robert C. Williamson and
Iven M.Y. Mareels, Hasty Congregational Gradient
Descent,",
shortened version submitted to IEEE Conference on Decision and
Control, 2000 (invited
session) but session was rejected. The link is to the full version
which was never actually submitted (if I recall correctly). The work
was completed around 1996.
[P104]
Alex J. Smola, Robert C. Williamson and Bernhard Schölkopf,
"Generalization Bounds for Convex Combinations of Kernel
Functions," Submitted to NIPS'98. NIPS did not like it. It has
evolved into P120.
[P113] Bernhard Schölkopf, Alex J. Smola and Robert C.
Williamson, "A New Parametrization of Support Vector Machines,"
submitted to the 4th European Conference on
Computational Learning Theory (EUROCOLT'99). EUROCOLT did not like
this. We turned it into P115.
Papers In Preparation
[P87]
Mario Marchand, John Shawe-Taylor and Robert C. Williamson,
"Choosing Hyperplanes to Improve Generalization,"
In Preparation. 1996-7.
[P99]
Robert C. Williamson, Bernhard Schölkopf and Alex Smola,
"A Maximum Margin Miscellany", February 1999. (35 pages)
[P109]
Robert C. Williamson, "Some Results in Statistical
learning Theory with Relevance to Nonlinear System
Identification," in preparation for submission to
Automatica August 1998. This paper is based on [P96], and was
invited to be submitted to Automatica. (Update 2005; I never
completed this; you can see an advanced
draft.
File translated from
TEX
by
TTH,
version 3.67.
On 23 May 2005, 00:26.