PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Peter Auer

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Number of EPrints submitted by this user: 21

Weak hypotheses and boosting for generic object detection and recognition
Andreas Opelt, Michael Fussenegger, Axel Pinz and Peter Auer
In: ECCV 2004, 11-14 May 2004, Prague, Czech Republic.

Generic object recognition with boosting
Andreas Opelt, Michael Fussenegger, Axel Pinz and Peter Auer
(2004) Technical Report. Graz University of Technology, Graz, Austria.

Object recognition using segmentation for feature detection (ICPR)
Michael Fussenegger, Andreas Opelt, Axel Pinz and Peter Auer
In: ICPR 2004, 23-26 Aug 2004, Cambridge, UK.

Object recognition using segmentation for feature detection (OeAGM)
Michael Fussenegger, Andreas Opelt, Axel Pinz and Peter Auer
In: ÖAGM 2004, 17-18 Jun 2004, Hagenberg, Austria.

Learning Theory, 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, Proceedings
Peter Auer and Ron Meir, ed. (2005) LNCS , Volume 3559 . Springer . ISBN 3-540-26556-2

On the loss version of the adversarial multi-armed bandit problem
Chamy Allenberg and Peter Auer
(2005) Working Paper. no.

Generic object recognition with boosting
Andreas Opelt, Michael Fussenegger, Axel Pinz and Peter Auer
IEEE PAMI 2005.

A learning rule for very simple universal approximators consisting of a single layer of perceptrons
Peter Auer, Harald Burgsteiner and Wolfgang Maass
(2005) Working Paper. no.

Boosting and Noisy Data - Outlier Detection and Removal
Thomas Jaksch
(2005) Masters thesis, University of Technology Graz.

Models for Trading Exploration and Exploitation using Upper Confidence Bounds
Peter Auer
In: EU PASCAL Workshop on "Principled methods of trading exploration and exploitation", 6-7 Jul 2005, London, UK.

Competitive Reinforcement Learning
Peter Auer
In: Models of Behavioural Learning Workshop (at NIPS 2005), 10 Dec 2005, Whistler, Canada.

Hannan consistency in on-line learning in case of unbounded losses under partial monitoring
Chamy Allenberg, Peter Auer, Laszlo Györfi and György Ottucsak
Algorithmic Learning Theory, ALT 2006 Number LNCS 4264, pp. 229-243, 2006.

A distributed voting scheme to maximize preferences
Peter Auer and Nicolò Cesa-Bianchi
RAIRO - Theoretical Informatics and Applications Volume 40, pp. 389-403, 2006.

Learning with Malicious Noise
Peter Auer
(2007) Springer.

On-line Learning
Peter Auer
(2007) Springer.

A learning rule for very simple universal approximators consisting of a single layer of perceptrons
Peter Auer, Harald Burgsteiner and Wolfgang Maass
Neural networks Volume 21, pp. 786-795, 2008.

Learning with Malicious Noise
Peter Auer
In: Encyclopedia of Algorithms (2008) Springer , pp. 1-99. ISBN 978-0-387-30770-1

Analysis of Optimistic Algorithms for the Exploration/Exploitation Trade-Off
Peter Auer
In: Foundations of Computational Mathematics, Hongkong(2008).

A Machine Learning (Theory) Perspective on Computer Vision
Peter Auer
In: History of Computer Vision, Graz, Austria(2008).

On-line Learning
Peter Auer
(2007) Springer.

On-line Learning
Peter Auer
(2010) Springer.