Robert C. Williamson

According to our database1, Robert C. Williamson authored at least 105 papers between 1990 and 2018.

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2018
Constant Regret, Generalized Mixability, and Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The cost of fairness in binary classification.
Proceedings of the Conference on Fairness, Accountability and Transparency, 2018

2017
A Theory of Learning with Corrupted Labels.
Journal of Machine Learning Research, 2017

f-GANs in an Information Geometric Nutshell.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Composite Multiclass Losses.
Journal of Machine Learning Research, 2016

Bipartite Ranking: a Risk-Theoretic Perspective.
Journal of Machine Learning Research, 2016

2015
Fast rates in statistical and online learning.
Journal of Machine Learning Research, 2015

Learning with Symmetric Label Noise: The Importance of Being Unhinged.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Generalized Mixability via Entropic Duality.
Proceedings of The 28th Conference on Learning Theory, 2015

Exp-Concavity of Proper Composite Losses.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
From Stochastic Mixability to Fast Rates.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

The Geometry of Losses.
Proceedings of The 27th Conference on Learning Theory, 2014

Elicitation and Identification of Properties.
Proceedings of The 27th Conference on Learning Theory, 2014

On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems.
Proceedings of The 27th Conference on Learning Theory, 2014

Bayes-Optimal Scorers for Bipartite Ranking.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Loss Functions.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
Clustering: Science or Art?
Proceedings of the Unsupervised and Transfer Learning, 2012

Divergences and Risks for Multiclass Experiments.
Proceedings of the COLT 2012, 2012

Mixability in Statistical Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

The Convexity and Design of Composite Multiclass Losses.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Information, Divergence and Risk for Binary Experiments.
Journal of Machine Learning Research, 2011

Mixability is Bayes Risk Curvature Relative to Log Loss.
Proceedings of the COLT 2011, 2011

Composite Multiclass Losses.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Convexity of Proper Composite Binary Losses.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Composite Binary Losses.
Journal of Machine Learning Research, 2010

2009
Surrogate regret bounds for proper losses.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Generalised Pinsker Inequalities.
Proceedings of the COLT 2009, 2009

2008
Correction to "The Importance of Convexity in Learning With Squared Loss".
IEEE Trans. Information Theory, 2008

2007
The Need for Open Source Software in Machine Learning.
Journal of Machine Learning Research, 2007

2006
Particle Filter Design Using Importance Sampling for Acoustic Source Localisation and Tracking in Reverberant Environments.
EURASIP J. Adv. Sig. Proc., 2006

2005
Learning the Kernel with Hyperkernels.
Journal of Machine Learning Research, 2005

Learnability of Probabilistic Automata via Oracles.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

2003
Particle filtering algorithms for tracking an acoustic source in a reverberant environment.
IEEE Trans. Speech and Audio Processing, 2003

Online Bayes Point Machines.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2003

Loop removal from LDPC codes.
Proceedings of the Proceedings 2003 IEEE Information Theory Workshop, 2003

Experimental comparison of particle filtering algorithms for acoustic source localization in a reverberant room.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Channel equalization and the Bayes point machine.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Acoustic beamforming exploiting directionality of human speech sources.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2002
Exploiting sparsity in adaptive filters.
IEEE Trans. Signal Processing, 2002

Hyperkernels.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Particle filter beamforming for acoustic source localization in a reverberant environment.
Proceedings of the IEEE International Conference on Acoustics, 2002

Agnostic Learning Nonconvex Function Classes.
Proceedings of the Computational Learning Theory, 2002

Large Margin Classification for Moving Targets.
Proceedings of the Algorithmic Learning Theory, 13th International Conference, 2002

2001
Convergence of exponentiated gradient algorithms.
IEEE Trans. Signal Processing, 2001

Generalization performance of regularization networks and support vector machines via entropy numbers of compact operators.
IEEE Trans. Information Theory, 2001

Estimating the Support of a High-Dimensional Distribution.
Neural Computation, 2001

Regularized Principal Manifolds.
Journal of Machine Learning Research, 2001

Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms.
Journal of Machine Learning Research, 2001

Kernel Machines and Boolean Functions.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Online Learning with Kernels.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Algorithmic Luckiness.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Very low voltage power conversion.
Proceedings of the 2001 International Symposium on Circuits and Systems, 2001

2000
Equalization in an acoustic reverberant environment: robustness results.
IEEE Trans. Speech and Audio Processing, 2000

New Support Vector Algorithms.
Neural Computation, 2000

Regularization with Dot-Product Kernels.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

From Margin to Sparsity.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Error performance of a channel of known impulse response.
Proceedings of the IEEE International Conference on Acoustics, 2000

Entropy Numbers of Linear Function Classes.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
Finite sample properties of linear model identification.
IEEE Trans. Automat. Contr., 1999

Noise modeling for nearfield array optimization.
IEEE Signal Process. Lett., 1999

The Entropy Regularization Information Criterion.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Support Vector Method for Novelty Detection.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Beamforming for a source located in the interior of a sensor array.
Proceedings of the ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications, 1999

An analysis of the exponentiated gradient descent algorithm.
Proceedings of the ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications, 1999

Nearfield broadband adaptive beamforming.
Proceedings of the ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications, 1999

On the poor robustness of sound equalization in reverberant environments.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Entropy Numbers, Operators and Support Vector Kernels.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Regularized Principal Manifolds.
Proceedings of the Computational Learning Theory, 4th European Conference, 1999

Covering Numbers for Support Vector Machines.
Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999

1998
Structural Risk Minimization Over Data-Dependent Hierarchies.
IEEE Trans. Information Theory, 1998

On the Relationship Between Behavioural and Standard Methods for System Identification.
Automatica, 1998

Shrinking the Tube: A New Support Vector Regression Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Broadband beamforming using elementary shape invariant beampatterns.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

1997
Decision region approximation by polynomials or neural networks.
IEEE Trans. Information Theory, 1997

Sampling rate versus quantisation in speech coders.
Signal Processing, 1997

Correction to 'Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes'.
Neural Computation, 1997

An adaptive algorithm for broadband frequency invariant beamforming.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

A PAC Analysis of a Bayesian Estimator.
Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

1996
Efficient agnostic learning of neural networks with bounded fan-in.
IEEE Trans. Information Theory, 1996

The VC Dimension and Pseudodimension of Two-Layer Neural Networks with Discrete Inputs.
Neural Computation, 1996

Nearfield broadband frequency invariant beamforming.
Proceedings of the 1996 IEEE International Conference on Acoustics, 1996

A Framework for Structural Risk Minimisation.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

The Importance of Convexity in Learning with Squared Loss.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
An efficient calculation of the moments of matched and mismatched hidden Markov models.
IEEE Trans. Signal Processing, 1995

Characterization of threshold for single tone maximum likelihood frequency estimation.
IEEE Trans. Signal Processing, 1995

Existence and uniqueness results for neural network approximations.
IEEE Trans. Neural Networks, 1995

Lower Bounds on the VC Dimension of Smoothly Parameterized Function Classes.
Neural Computation, 1995

Neural networks, rational functions, and realization theory.
MCSS, 1995

Examples of learning curves from a modified VC-formalism.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

On Efficient Agnostic Learning of Linear Combinations of Basis Functions.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

Online Learning via Congregational Gradient Descent.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, 1995

1994
Performance of the maximum likelihood constant frequency estimator for frequency tracking.
IEEE Trans. Signal Processing, 1994

Conditional mean and maximum likelihood approaches to multiharmonic frequency estimation.
IEEE Trans. Signal Processing, 1994

Threshold effects in multiharmonic maximum likelihood frequency estimation.
Signal Processing, 1994

A simple calculation of the joint moments of hidden Markov models.
Proceedings of ICASSP '94: IEEE International Conference on Acoustics, 1994

Lower Bounds on the VC-Dimension of Smoothly Parametrized Function Classes.
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994

Fat-Shattering and the Learnability of Real-Valued Functions.
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994

1993
The relationship between instantaneous frequency and time-frequency representations.
IEEE Trans. Signal Processing, 1993

1992
The statistical performance of some instantaneous frequency estimators.
IEEE Trans. Signal Processing, 1992

Rational Parametrizations of Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991
An extreme limit theorem for dependency bounds of normalized sums of random variables.
Inf. Sci., 1991

Splines, Rational Functions and Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Investigating the Distribution Assumptions in the Pac Learning Model.
Proceedings of the Fourth Annual Workshop on Computational Learning Theory, 1991

1990
Probabilistic arithmetic. I. Numerical methods for calculating convolutions and dependency bounds.
Int. J. Approx. Reasoning, 1990

epsilon-Entropy and the Complexity of Feedforward Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 3, 1990


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