Onno Zoeter

Associate Researcher

Applied Games Group
Machine Learning and Perception
Microsoft Research Cambridge

onnoz [@] microsoft.com
7 J J Thomson Avenue
Cambridge, CB3 0FB
United Kingdom
Tel: +44 (0)1223 479 845


Research | Publications | Bio

Publications

  • Onno Zoeter (2008).
    On a form of advertiser cheating in sponsored search and a dynamic-VCG solution.
    In: Proceedings of TROA 2008. [pdf]
  • Nick Craswell, Onno Zoeter, Michael Taylor, and Bill Ramsey (2008).
    An experimental comparison of click position-bias models.
    In: Proceedings of WSDM 2008. [pdf]
  • Onno Zoeter, Nick Craswell, Michael Taylor, John Guiver, and Ed Snelson (2007).
    A decision theoretic framework for implicit relevance feedback.
    NIPS 2007 Workshop: Machine learning for web search. [pdf]
  • Onno Zoeter (2007).
    Bayesian generalized linear models in a terabyte world.
    In: Proceedings IEEE ISPA 2007 [ps]
  • Onno Zoeter, Alexander Ypma, and Tom Heskes, (2006).
    Deterministic and stochastic Gaussian particle smoothing.
    In: Proceedings NSSPW 2006 [pdf]
  • Onno Zoeter, and Tom Heskes, (2006).
    Deterministic approximate inference techniques for conditionally Gaussian state space models.
    Statistics and Computing 16:279-292 [journal site]
  • Onno Zoeter, and Tom Heskes, (2005).
    Changepoint problems in linear dynamical systems.
    Journal for Machine Learning Research (JMLR) 6: 1999-2026. [journal site]
    Slides from the Pascal workshop Optimization and Inference in Machine Learning and Physics, Lavin 2005. [pdf] [ps]
  • Tom Heskes, Manfred Opper, Wim Wiegerinck, Ole Winther, Onno Zoeter (2005).
    Approximate inference techniques with expectation constraints.
    In: Journal of Statistical Mechanics: Theory and Experiment, 2005:P11015 [pdf] [ps]
  • Onno Zoeter (2005).
    Monitoring non-linear and switching dynamical systems.
    Ph.D. Thesis, Radboud University Nijmegen [pdf][ps]
  • Onno Zoeter, and Tom Heskes, (2005).
    Gaussian Quadrature Based Expectation Propagation.
    In: Proceedings AISTATS 2005, eds. Z. Ghahramani and R. Cowell. [pdf][ps]
    Matlab code
  • Onno Zoeter, Alexander Ypma, and Tom Heskes, (2004).
    Improved unscented Kalman smoothing for stock volatility estimation.
    In: Proceedings of the IEEE workshop on Machine Learning for Signal Processing, eds. A. Barros, J. Principe, J. Larsen, T. Adali, and S. Douglas. [pdf][ps]
    Slides [pdf] [ps]
    Matlab code
  • Tom Heskes, Onno Zoeter, and Wim Wiegerinck (2004).
    Approximate Expectation Maximization.
    In: Proceedings NIPS 16. [ps.gz][pdf]
  • Onno Zoeter and Tom Heskes (2003).
    Hierarchical visualization of time-series data using switching linear dynamical systems.
    IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 25, No. 10, October 2003, pp. 1202-1215. [pdf][ps]
  • Onno Zoeter and Tom Heskes (2003).
    Multi-scale switching linear dynamical systems.
    In: Proceedings ICANN/ICONIP 2003. [pdf][ ps]
  • Tom Heskes and Onno Zoeter (2003).
    Generalized belief propagation for approximate inference in hybrid Bayesian networks.
    In: Proceedings AISTATS 2003, eds. C. Bishop and B. Frey. [ps, conference site] [pdf, conference site]
      Note: Section 4.2 with results on discrete children with continuous children has been adapted after "bug removal" yielded better performance and correspondence with previous work; many apologies for any confusion.
  • Tom Heskes and Onno Zoeter (2002).
    Expectation propagation for approximate inference in dynamic Bayesian networks.
    In: Proceedings UAI-2002, eds. A. Darwiche and N. Friedman, pp. 216-223. [ps.gz]
      Here is a technical report [ps.gz] that formed the basis of the conference paper. It contains more details, but is not fully compatible.