Gilles Blanchard
23 papers · 2003–2024 · 6 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (15) π Interdisciplinary Bridge π Conference Polyglot (6)
π§
Keyword Pioneer
π
Conference Polyglot
(6)
π
Keyword Trendsetter Combo
(4)
π
Keyword Champion
(2)
π
Century Club
(23)
ποΈ
Keyword Collector
(52)
π₯
Unstoppable
(6)
π
Trend Setter
π
Conference Pioneer
Conferences
JMLR (9)
NIPS (5)
AISTATS (4)
ALT (2)
COLT (2)
ICML (1)
Top co-authors
Research topics
Keywords
kernel methods
(6)
learning theory
(4)
reproducing kernel hilbert space
(4)
novelty detection
(3)
convergence rate
(3)
label noise
(3)
semi-supervised learning
(2)
conjugate gradient
(2)
learning rate
(2)
early stopping
(2)
multiple kernel learning
(2)
transfer learning
(2)
excess risk bound
(2)
graph laplacian
(1)
spectral clustering
(1)
statistical consistency
(1)
manifold learning
(1)
binary classification
(1)
multi-task learning
(1)
dimensionality reduction
(1)
Papers
Transductive conformal inference with adaptive scores
AISTATS 2024
Covariance-adaptive best arm identification
NIPS 2023
Constant regret for sequence prediction with limited advice
ALT 2023
Topologically penalized regression on manifolds
JMLR 2022
Fast rates for prediction with limited expert advice
NIPS 2021
Domain Generalization by Marginal Transfer Learning
JMLR 2021
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding
AISTATS 2021
A minimax near-optimal algorithm for adaptive rejection sampling
ALT 2019
Decontamination of Mutual Contamination Models
JMLR 2019
Parallelizing Spectrally Regularized Kernel Algorithms
JMLR 2018
Localized Complexities for Transductive Learning
COLT 2014
Decontamination of Mutually Contaminated Models
AISTATS 2014
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation
ICML 2014
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
COLT 2013
On the Convergence Rate of -Norm Multiple Kernel Learning
JMLR 2012
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning
NIPS 2011
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample
NIPS 2011
Semi-Supervised Novelty Detection
JMLR 2010
Optimal learning rates for Kernel Conjugate Gradient regression
NIPS 2010
Kernel Partial Least Squares is Universally Consistent
AISTATS 2010
Adaptive False Discovery Rate Control under Independence and Dependence
JMLR 2009
In Search of Non-Gaussian Components of a High-Dimensional Distribution
JMLR 2006
On the Rate of Convergence of Regularized Boosting Classifiers
JMLR 2003