PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Jean-Yves Audibert

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Number of EPrints submitted by this user: 31

Graph Laplacians and their convergence on random neighborhood graphs
Matthias Hein, Jean-Yves Audibert and Ulrike Von Luxburg
Journal of Machine Learning Research Volume 8, pp. 1325-1368, 2007.

Combining PAC-Bayesian and generic chaining bounds
Jean-Yves Audibert and Olivier Bousquet
Journal of Machine Learning Research Volume 8, pp. 863-889, 2007. ISSN 1533-7928

Fast learning rates for plug-in classifiers
Jean-Yves Audibert and Alexandre Tsybakov
The Annals of Statistics Volume 35, Number 2, pp. 608-633, 2007.

Progressive mixture rules are deviation suboptimal
Jean-Yves Audibert
In: NIPS 2007, 3-6 Dec 2007, Vancouver, Canada.

Manifold-Adaptive Dimension Estimation
Amir massoud Farahmand, Csaba Szepesvari and Jean-Yves Audibert
In: ICML 2007, 20-24 Jun 2007, USA.

Graph-cut transducers for relevance feedback in content based image retrieval
Hichem Sahbi, Jean-Yves Audibert and Renaud Keriven
In: ICCV 2007, 14-20 Oct 2007, Brésil.

Tuning Bandit Algorithms in Stochastic Environments
Jean-Yves Audibert, Remi Munos and Csaba Szepesvari
In: ALT 2007, 1-4 Oct 2007, Japon.

Some links between min-cuts, optimal spanning forests and watersheds
Cedric Allene, Jean-Yves Audibert, Michel Couprie, Jean Cousty and Renaud Keriven
In: ISMM 2007, 10-13 Oct 2007, Bresil.

Fast learning rates for plug-in classifiers under the margin condition
Jean-Yves Audibert
In: Empirical Processes and Asymptotic Statistics 2007, Jun 2007, Rennes, France.

Aggregation to compete the best prediction function in a finite set
Jean-Yves Audibert
In: Probability and Statistics in Science and Technology, ISI 2007, Sep 2007, Porto, Portugal.

Convergence of the graph Laplacian: application to dimensionality estimation and image segmentation
Jean-Yves Audibert
In: Graph Theory and Machine learning Workshop, 2007, Jun 2007, Bled, Slovenia.

Graph-based methods for manifold learning
Jean-Yves Audibert
In: Mathematics for biological networks, 17-18 Dec 2007, Paris, France.

Toward Manifold-Adaptive Learning
Amir massoud Farahmand, Csaba Szepesvari and Jean-Yves Audibert
In: NIPS 2007, Dec 2007, Whistler, Canada.

Exploration-exploitation tradeoff using variance estimates in multi-armed bandits
Jean-Yves Audibert, Rémi Munos and Csaba Szepesvari
Theoretical Computer Science 2008.

Algorithms for infinitely many-armed bandits
Yizao Wang, Jean-Yves Audibert and Rémi Munos
In: NIPS 2008, 8-13 Dec 2008, Vancouver, Canada.

Fast learning rates in statistical inference through aggregation
Jean-Yves Audibert
Annals of Statistics 2007.

Semantic lattices for multiple annotation of images
Anne-Marie Tousch, Stéphane Herbin and Jean-Yves Audibert
In: MIR 2008, 30-31 Oct 2008, Vancouver, Canada.

Empirical Bernstein stopping
Volodymyr Mnih, Csaba Szepesvari and Jean-Yves Audibert
In: ICML 2008, 5-9 Jul 2008, Helsinki, Finlande.

Robust matching and recognition using context-dependent kernels
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabarisoa and Renaud Keriven
In: ICML 2008, 5-9 Jul 2008, Helsinki, Finlande.

Object recognition and retrieval by context dependent similarity kernels
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabarisoa and Renaud Keriven
In: CBMI 2008, 18-20 Jun 2008, London, UK.

Segmentation by transduction
Olivier Duchenne, Jean-Yves Audibert, Renaud Keriven, Jean Ponce and Florent Ségonne
In: CVPR 2008, 24-26 Jun 2008, Alaska, US.

Manifold learning using robust graph Laplacian for interactive image retrieval
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert and Renaud Keriven
In: CVPR 2008, 24-26 Jun 2008, Alaska, US.

Context-dependent kernel design for object matching and recognition
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabarisoa and Renaud Keriven
In: CVPR 2008, 24-26 Jun 2008, Alaska, US.

Graph Laplacian for interactive image retrieval
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert and Renaud Keriven
In: ICASSP 2008, 30 Mar - 04 Apr 2008, Nevada, US.

Transductive learning and computer vision
Jean-Yves Audibert
In: NIPS 2008 Workshop on Learning with Data-dependent Concept Spaces, 8-13 Dec 2008, Vancouver, Canada.

Supervised learning for computer vision: theory and algorithms
Francis Bach and Jean-Yves Audibert
In: ECCV 2008, 12 - 18 Oct 2008, Marseille, France.

General road detection from a single image
Hui Kong, Jean-Yves Audibert and Jean Ponce
Transactions on Image Processing 2009.

Detecting Abandoned Objects with a Moving Camera
Hui Kong, Jean-Yves Audibert and Jean Ponce
Transactions on Image Processing 2009.

Metric Entropy and Gaussian Bandits
Steffen Grunewalder, Jean-Yves Audibert, Manfred Opper and John Shawe-Taylor
In: Nonparametric Bayes Workshop at NIPS 2009, 12 Dec 2009, Whistler, Cznada.

Vanishing point detection for road detection
Hui Kong, Jean-Yves Audibert and Jean Ponce
In: CVPR 2009, 20-25 Jun 2009, Miami, USA.

Transductive segmentation of textured meshes
Anne-Laure Chauve, Jean-Philippe Pons, Jean-Yves Audibert and Renaud Keriven
In: ACCV 2009, 23-27 Sep 2009, Xi' an, China.