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- Gilles Blanchard, Benjamin Blankertz
- IEEE Transactions on Biomedical Engineering
- 2004

A brain-computer interface (BCI) is a system that should in its ultimate form translate a subject's intent into a technical control signal without resorting to the classical neuromuscularâ€¦ (More)

- Gilles Blanchard, Gyemin Lee, Clayton Scott
- Journal of Machine Learning Research
- 2010

A common setting for novelty detection assumes that labeled xamples from the nominal class are available, but that labeled examples of novelties are un available. The standard (inductive) approach isâ€¦ (More)

- Gilles Blanchard, Olivier Bousquet, Laurent Zwald
- Machine Learning
- 2006

The main goal of this paper is to prove inequalities on the reconstruction error for kernel principal component analysis. With respect to previous work on this topic, our contribution is twofold: (1)â€¦ (More)

The support vector machine (SVM) algorithm is well known to the computer learning community for its very good practical results. The goal of the present paper to study this algorithm from aâ€¦ (More)

- Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert MÃ¼ller
- Journal of Machine Learning Research
- 2006

Finding non-Gaussian components of high-dimensional data is an important preprocessing step for efficient information processing. This article proposes a new linear method to identify theâ€¦ (More)

- Gilles Blanchard, Gyemin Lee, Clayton Scott
- NIPS
- 2011

The function k : Î©Ã—Î©â†’ R is called a kernel on Î© if the matrix (k(xi, xj))1â‰¤i,jâ‰¤n is positive semidefinite for all positive integers n and all x1, . . . , xn âˆˆ Î©. It is well-known that if k is aâ€¦ (More)

- Gilles Blanchard, Nicole MÃ¼cke
- Foundations of Computational Mathematics
- 2018

We consider a statistical inverse learning problem, where we observe the image of a function f through a linear operator A at i.i.d. random design points Xi, superposed with an additive noise. Theâ€¦ (More)

- Laurent Zwald, Gilles Blanchard
- NIPS
- 2005

This paper presents a non-asymptotic statistical analysis of Kernel-PCA with a focus different from the one proposed in previous work on this topic. Here instead of considering the reconstructionâ€¦ (More)

- Gilles Blanchard, GÃ¡bor Lugosi, Nicolas Vayatis
- Journal of Machine Learning Research
- 2003

A regularized boosting method is introduced, for which regularization is obtained through a penalization function. It is shown through oracle inequalities that this method is model adaptive. The rateâ€¦ (More)

We explore the theoretical foundations of a " twenty questions " approach to pattern recognition. The object of the analysis is the computational process itself rather than probability distributionsâ€¦ (More)