Publications

2010

  1. M. Pfeiffer: Concepts and methods from machine learning as tools for the analysis of computations in nervous systems. PhD Thesis. February 2010.

2009

  1. B. Nessler, M. Pfeiffer, and W. Maass: STDP enables spiking neurons to detect hidden causes of their inputs. Proceedings of NIPS-22, Vancouver, Canada. December 2009. (PDF)
  2. M. Pfeiffer, B. Nessler, R. Douglas, and W. Maass: Reward-modulated Hebbian Learning of Decision Making. Neural Computation, in press. (Abstract)

2008

  1. B. Nessler, M. Pfeiffer, and W. Maass: Hebbian learning of Bayes optimal decision. Proceedings of NIPS-21, Vancouver, Canada. December 2008. (Abstract), (PDF)
  2. M. Pfeiffer, B. Nessler, and W. Maass: A Hebbian learning rule for optimal decision making. Poster at Workshop on Machine Learning meets Human learning, Whistler, Canada. December 2008.

2007

  1. G. Neumann, M. Pfeiffer, and W. Maass: Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs. Proceedings of ECML-18, Warszaw, Poland. September 2007. (PDF)

2005

  1. M. Pfeiffer, A. Saffari A.A., A. Juffinger: Predicting Text Relevance from Sequential Reading Behavior. Proceedings of NIPS Workshop on Implicit Feedback and User Modeling, Whistler, Canada. December 2005. (Winner of PASCAL Challenge "Inferring Relevance from Eye Movements", Competition One) (PDF)

2004

  1. M. Pfeiffer: Reinforcement Learning of Strategies for Settlers of Catan, Proceedings of the International Conference on Computer Games: Artificial Intelligence, Design and Education, Reading, UK. November 2004. (Best Paper Award Nominee) (PDF)
  2. M. Pfeiffer: Machine Learning Applications in Computer Games, ÖGAI-Journal 23 (2004), Nr.3.

2003

  1. M. Pfeiffer: Machine Learning Applications in Computer Games. Master's Thesis, Institute for Theoretical Computer Science, Graz University of Technology. June 2003. (PDF)

Presentations

2006

  1. M. Pfeiffer: Theories about Dopamine. Seminar Talk, January 2006.
  2. M. Pfeiffer: Reinforcement Learning: A Tutorial. Seminar Talk, March 2006.

2005

  1. M. Pfeiffer: Convergence Proofs for Reinforcement Learning with Function Approximation. Seminar Talk, January 2005. (PDF)
  2. M. Pfeiffer, A. Saffari A.A., A. Juffinger: Predicting Text Relevance from Sequential Reading Behavior. NIPS Workshop on Machine Learning for Implicit Feedback and User Modeling, December 2005.

2004

  1. M. Pfeiffer: Reinforcement Learning for Motor Control. Seminar Talk, January 2004. (PPT)
  2. M. Pfeiffer: A brief Introduction to Particle Filters. Journal Club Talk, May 2004. (PPT)(PDF)
  3. C. Strecha, R. Fransens, L. van Gool: Wide-baseline Stereo from Multiple Views: a Probabilistic Account. Seminar Talk, June 2004. (PDF)
  4. M. Pfeiffer: Opponent Modelling and Plan Recognition. Seminar Talk, July 2004. (PDF)
  5. M. Pfeiffer: Reinforcement Learning of Strategies for Settlers of Catan. Conference Talk at the International Conference on Computer Games: Artificial Intelligence, Design and Education, Reading, UK. November 2004. (PPT)(PDF)
  6. T. Poggio, R. Rifkin, S. Mukherjee, P. Niyogi: General Conditions for Predictivity in Learning Theory. Seminar Talk, November 2004. (PDF)(PPT)

2003

  1. M. Weber, M. Welling, L. Fei-Fei, R. Fergus, P. Perona: Unsupervised Learning of Visual Object Categories. Journal Club Talk, November 2003. (PPT)(PDF)
  2. M. Pfeiffer: Künstliche Intelligenz und Maschinelles Lernen in Computerspielen (German only). Lecture for Machine Learning A, December 2003. (PPT)

Technical Reports

  1. M. Pfeiffer: Readout, Feedback and Physical Model Tool (for CSIM). (PDF)

Last Updated: 22-02-2010