Ole Winther - preprints and publications

All newer papers can be found in ORBIT the DTU research database by searching for me here.

Older stuff:

My IMM publications (including BibTex etc.) can also be found here. Other BibTex files etc. can be send upon request.

Preprints

Flexible and Efficient Implementations of Bayesian Independent Component Analysis
O. Winther and K. B. Petersen
Submitted to Neurocomputing
Download pdf icaMF Matlab toolbox v3 beta
Frame Selection for Speaker Identification
Maïa Weddin and Ole Winther
Submitted to ICASSP'2006 (2005).
Download pdf More info including bibTEX
Analysis of Mean Field Annealing in Subtractive Interference Cancellation
Thomas Fabricius and Ole Winther
Submitted to IEEE Transactions on Communications (2002).
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Publications

Robust Multi-scale Clustering of Large DNA Microarray Datasets with the Consensus Algorithm
T. Grotkjær, O. Winther, B. Regenberg, J. Nielsen and L. K. Hansen
Bioinformatics 22, 58-67 (2006)
Download pdf More info including bibTEX + supplementary material ClusterLustre v.1.2 Matlab software
Approximate Inference Techniques with Expectation Constraints
T. Heskes, M. Opper, W. Wiegerinck, O. Winther and O. Zoeter
Journal of Statistical Mechanics: Theory and Experiment, 11015 (2005)
Download pdf More info including BibTex
Expectation Consistent Approximate Inference
M. Opper and O. Winther
Journal of Machine Learning Research 6, 2177-2204 (2005)
Download pdf More info including BibTex + matlab code
On the Slow Convergence of EM and VBEM in Low-Noise Linear Models
K. B. Petersen, O. Winther and L. K. Hansen
Neural Computation 17, 1921-1926 (2005)
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Approximate Inference in Probabilistic Models
M. Opper and O. Winther
Lecture Notes in Artificial Intelligence 3244, 494-504 (2004)
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Expectation Consistent Free Energies for Approximate Inference
Manfred Opper and Ole Winther
In Advances in Neural Information Processing Systems 17 (NIPS'2004).
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The EM Algorithm in Independent Component Analysis
K. B. Petersen and O. Winther
IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP (2005).
Download pdf More info including bibTEX
Teaching Computers to Fold Proteins
Ole Winther and Anders Krogh
Physical Review E 70, 030903 (2004) and October 1, 2004 issue of Virtual Journal of Biological Physics Research..
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Download supporting information ps.gz Download supporting information pdf
Low Complexity Bayesian Single Channel Source Separation
Thomas Beierholm, Brian Dam Pedersen and Ole Winther
ICASSP (2003).
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Download sound demo zip
Variational Linear Response
Manfred Opper and Ole Winther
In Advances in Neural Information Processing Systems 16 (NIPS'2003).
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Tractable Inference for Probabilistic Data Models
Lehel Csato, Manfred Opper and Ole Winther
Complexity 8, no. 4, p. 64-68 (2003).
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Improved Multistage Detector by Mean-Field Annealing in Multi-User CDMA
Thomas Fabricius and Ole Winther
In Proceedings of IEEE Intelligent Signal Processing, Applications, and Communication Systems (2002).
Download pdf
Incremental Gaussian Processes
Joaquin Quiñonero Candela and Ole Winther
In Advances in Neural Information Processing Systems 15 (NIPS'2002).
S. Becker, S. Thrun, and K. Obermayer, eds., MIT Press (2003).
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Independent Component Analysis for Understanding Multimedia Content
T. Kolenda, L. K. Hansen, J. Larsen and O. Winther
in Proceedings of IEEE Workshop on Neural Networks for Signal Processing XII
H. Bourlard, T. Adali, S. Bengio, J. Larsen, and S. Douglas, eds., IEEE Press (2002).
Download pdf
Analysis of Functional Neuroimages Using ICA Adaptive Binary Sources
P.A.d.F.R. Højen-Sørensen, O. Winther and L. K. Hansen
Neurocomputing 49 (1-4), 213-225 (2002).
TAP Gibbs Free Energy, Belief Propagation and Sparsity
L. Csato, M. Opper and O. Winther
In Advances in Neural Information Processing Systems 14 (NIPS'2001)
T. G. Dietterich, S. Becker and Z. Ghahramani, eds., MIT Press (2002).
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Mean Field Approaches to Independent Component Analysis
Pedro A.d.F.R. Højen-Sørensen, Ole Winther and Lars Kai Hansen
Neural Computation 14, 889-918 (2002).
Download ps.gz Download pdf Download matlab code - the DTU ICA toolbox
Mean Field Implementation of Bayesian ICA
P.A.d.F.R. Højen-Sørensen, L. K. Hansen and O. Winther
In proceedings of 3rd International Conference on Independent Component Analysis and Blind Signal Separation (ICA2001), Institute of Neural Computation (2001).
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Probabilistic Data Modeling with Adaptive TAP Mean Field Theory
M. Opper and O. Winther
Physica A 302 (1-4), 119-125 (2001).
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Adaptive and Self-averaging Thouless-Anderson-Palmer Mean Field Theory for Probabilistic Modeling
M. Opper and O. Winther
Physical Review E 64, 056131 (2001).
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Computing with Finite and Infinite Networks
O. Winther
In Advances in Neural Information Processing Systems 13 (NIPS'2000), eds. T. K. Leen, T. G. Dietterich and V. Tresp, 336-342, MIT Press (2001).
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Ensemble Learning and Linear Response Theory for ICA
P. A.d.F.R. Højen-Sørensen, O. Winther and L. K. Hansen
In Advances in Neural Information Processing Systems 13 (NIPS'2000), eds. T. K. Leen, T. G. Dietterich and V. Tresp, 542-548, MIT Press (2001).
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From Naive Mean Field Theory to the TAP Equations
M. Opper and O. Winther
In Advanced Mean Field Methods - Theory and Practice, eds. M. Opper and D. Saad, 7-20, MIT Press (2001).
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Adaptive TAP Equations
M. Opper and O. Winther
In Advanced Mean Field Methods - Theory and Practice, eds. M. Opper and D. Saad, 85-98, MIT Press (2001).
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Tractable Approximations for Probabilistic Models: The Adaptive Thouless-Anderson-Palmer Mean Field Approach
M. Opper and O. Winther
Phys. Rev. Lett. 86, 3695-3699 (2001).
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Gaussian Processes for Classification: Mean Field Algorithms
M. Opper and O. Winther
Neural Computation, 12, 2655-2684 (2000).
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Efficient Approaches to Gaussian Process Classification
L. Csato, E. Fokoue, M. Opper, B. Schottky and O. Winther
In Advances in Neural Information Processing Systems 12 (NIPS'99), Eds. S. A. Solla , T. K. Leen, and K.-R. Muller, 251-257, MIT Press (2000).
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Gaussian Processes and SVM: Mean Field Results and Leave-One-Out
M. Opper and O. Winther
In Advances in Large Margin Classifiers, Eds. A. J. Smola, P. Bartlett, B. Sch lkopf, D. Schuurmans, 311-326, MIT Press (2000).
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Optimal Online Learning: a Bayesian Approach
S. A. Solla and O. Winther
Computer Physics Communication, 121-122, 94-97 (1999).
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Mean field Methods for Classification with Gaussian Processes
M. Opper and O. Winther
In Advances in Neural Information Processing Systems 11 (NIPS'98), Eds. M. S. Kearns, S. A. Solla, and D. A. Cohn, 309-315, MIT Press (1999).
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Optimal Perceptron Learning: an Online Bayesian Approach
S. A. Solla and O. Winther
In Proceedings of the Newton Institute Workshop on On-Line Learning, Ed. D. Saad , 379-398, Cambridge University Press (1998).
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Optimal Bayesian Online Learning
O. Winther and S. A. Solla
Theoretical Aspects of Neural Computation (TANC'97), Eds. K.-Y. M. Wong, I. King, and D.-Y. Yeung, 61-70, Springer Singapore (1998).
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Bayesian Online Learning in the Perceptron
O. Winther and S. A. Solla
European Symposium on Artificial Neural Networks (ESANN'97), Ed. M. Verleysen , 167-172, D Facto, Brussels (1997).
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A Mean Field Algorithm for Bayes Learning in Large Feed-Forward Neural Networks
M. Opper and O. Winther
In Advances in Neural Information Processing Systems 9, Eds. M. C. Mozer, M. I. Jordan, and T. Petsche, 225-331, MIT Press (1997).
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The Effect of Correlated Input Data on the Dynamics of Learning
S. Halkjaer and O. Winther
In Advances in Neural Information Processing Systems 9, Eds. M. C. Mozer, M. I. Jordan, and T. Petsche, 169-175, MIT Press (1997).
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Optimal learning in Multilayer Neural Networks
O. Winther, B. Lautrup, and J-B. Zhang
Physical Review E 55, 836 (1997).
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A Mean Field Approach to Bayes Learning in Feed-Forward Neural networks
M. Opper and O. Winther
Physical Review Letters 76, 1964 (1996)
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Learning to Classify in Large Committee Machines
D. O'Kane and O. Winther
Phys. Rev. E 50, 3201-3209 (1994).
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Neural Networks and Cellular Automata Complexity
J. Gorodkin, A. Sørensen and O. Winther
Complex Systems 7, 1-23, (1993).
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A Quantitative Study of Pruning by Optimal Brain Damage
J. Gorodkin, A. Krogh, L. K. Hansen, C. Svarer and O. Winther
Int. Jour. of Neural Systems 4, 159-169, (1993).
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Ph.D. thesis

Bayesian Mean Field Algorithms for Neural Networks and Gaussian Processes
O. Winther
University of Copenhagen, May 1998.
Download ps.gz Download pdf Hardcopy available upon request.

Technical Reports

Correcting the Bias of Subtractive Interference Cancellation in CDMA: Advanced Mean Field Theory
Thomas Fabricius and Ole Winther
Manuscript (2003).
Download ps.gz Download pdf Download matlab code
Large Scale Bayesian Kernel Learning with Subspace EM Algorithm
Joaquin Quiñonero Candela and Ole Winther
Technical report (2002).
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Recent talks and posters

Efficient Approaches to Gaussian Process Classification
L. Csato, E. Fokoue, M. Opper, B. Schottky and O. Winther
Spotlight poster presentation at NIPS'99.
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Mean Field Methods for Classification with Gaussian Processes
M. Opper and O. Winther
Oral presentation at NIPS'98.
Download ps.gz Download pdf <- Talk
Download ps.gz Download pdf <- Poster
Mean Field Algorithm for Gaussian Process Classification and Support Vector Machines
O. Winther and M. Opper
Talk at the NIPS'98 Workshop on Large Margin Classifiers.
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Last updated 22nd December 2005

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