Matthias Hein

Yannic Neuhaus

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Nonlinear Perron-Frobenius Theorems for Nonnegative Tensors.

[BibT_eX]

[DOI]

SIAM Rev., May, 2023

Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators.

[BibT_eX]

[DOI]

Nandhini Chandramoorthy

IEEE Trans. Pattern Anal. Mach. Intell., March, 2023

Analyzing and Explaining Image Classifiers via Diffusion Guidance.

[BibT_eX]

[DOI]

Yannic Neuhaus

CoRR, 2023

Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2023

Robust Semantic Segmentation: Strong Adversarial Attacks and Fast Training of Robust Models.

[BibT_eX]

[DOI]

Naman D. Singh

CoRR, 2023

Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models.

[BibT_eX]

[DOI]

Naman Deep Singh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Normalization Layers Are All That Sharpness-Aware Minimization Needs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving l1-Certified Robustness via Randomized Smoothing by Leveraging Box Constraints.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation.

[BibT_eX]

[DOI]

Maximilian Müller

Proceedings of the International Conference on Machine Learning, 2023

A Modern Look at the Relationship between Sharpness and Generalization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Sound Randomized Smoothing in Floating-Point Arithmetic.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

On the Adversarial Robustness of Multi-Modal Foundation Models.

[BibT_eX]

[DOI]

Christian Schlarmann

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Identifying Systematic Errors in Object Detectors with the SCROD Pipeline.

[BibT_eX]

[DOI]

Valentyn Boreiko

Jan Hendrik Metzen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

On the interplay of adversarial robustness and architecture components: patches, convolution and attention.

[BibT_eX]

[DOI]

CoRR, 2022

Sound Randomized Smoothing in Floating-Point Arithmetics.

[BibT_eX]

[DOI]

CoRR, 2022

Neural Network Heuristic Functions: Taking Confidence into Account.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth International Symposium on Combinatorial Search, 2022

Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Diffusion Visual Counterfactual Explanations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations.

[BibT_eX]

[DOI]

Jan Nikolas Morshuis

Sergios Gatidis

Christian F. Baumgartner

Proceedings of the Machine Learning for Medical Image Reconstruction, 2022

Visual Explanations for the Detection of Diabetic Retinopathy from Retinal Fundus Images.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Provably Adversarially Robust Nearest Prototype Classifiers.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Evaluating the Adversarial Robustness of Adaptive Test-time Defenses.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Adversarial Robustness against Multiple and Single lp-Threat Models via Quick Fine-Tuning of Robust Classifiers.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Sparse Visual Counterfactual Explanations in Image Space.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition, 2022

Being a Bit Frequentist Improves Bayesian Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks.

[BibT_eX]

[DOI]

Naman D. Singh

Nicolas Flammarion

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

The Global Convergence of the Nonlinear Power Method for Mixed-Subordinate Matrix Norms.

[BibT_eX]

[DOI]

J. Sci. Comput., 2021

Provably Robust Detection of Out-of-distribution Data (almost) for free.

[BibT_eX]

[DOI]

CoRR, 2021

Adversarial robustness against multiple lp-threat models at the price of one and how to quickly fine-tune robust models to another threat model.

[BibT_eX]

[DOI]

CoRR, 2021

Learnable uncertainty under Laplace approximations.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks.

[BibT_eX]

[DOI]

Maksym Yatsura

Jan Hendrik Metzen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

RobustBench: a standardized adversarial robustness benchmark.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Bit Error Robustness for Energy-Efficient DNN Accelerators.

[BibT_eX]

[DOI]

Nandhini Chandramoorthy

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

Mind the Box: l1-APGD for Sparse Adversarial Attacks on Image Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Relating Adversarially Robust Generalization to Flat Minima.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks.

[BibT_eX]

[DOI]

Jonas Rauber

Int. J. Comput. Vis., 2020

Error Estimates for Spectral Convergence of the Graph Laplacian on Random Geometric Graphs Toward the Laplace-Beltrami Operator.

[BibT_eX]

[DOI]

Nicolás García Trillos

Moritz Gerlach

Dejan Slepcev

Found. Comput. Math., 2020

Out-distribution aware Self-training in an Open World Setting.

[BibT_eX]

[DOI]

CoRR, 2020

RobustBench: a standardized adversarial robustness benchmark.

[BibT_eX]

[DOI]

CoRR, 2020

Fixing Asymptotic Uncertainty of Bayesian Neural Networks with Infinite ReLU Features.

[BibT_eX]

[DOI]

CoRR, 2020

Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data.

[BibT_eX]

[DOI]

CoRR, 2020

On Mitigating Random and Adversarial Bit Errors.

[BibT_eX]

[DOI]

Nandhini Chandramoorthy

CoRR, 2020

Computing the norm of nonnegative matrices and the log-Sobolev constant of Markov chains.

[BibT_eX]

[DOI]

CoRR, 2020

Certifiably Adversarially Robust Detection of Out-of-Distribution Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Towards neural networks that provably know when they don't know.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Adversarial Robustness on In- and Out-Distribution Improves Explainability.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search.

[BibT_eX]

[DOI]

Nicolas Flammarion

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

A Unifying Perron-Frobenius Theorem for Nonnegative Tensors via Multihomogeneous Maps.

[BibT_eX]

[DOI]

SIAM J. Matrix Anal. Appl., 2019

The Perron-Frobenius Theorem for Multihomogeneous Mappings.

[BibT_eX]

[DOI]

SIAM J. Matrix Anal. Appl., 2019

Confidence-Calibrated Adversarial Training: Towards Robust Models Generalizing Beyond the Attack Used During Training.

[BibT_eX]

[DOI]

CoRR, 2019

Provable robustness against all adversarial lp-perturbations for p≥1.

[BibT_eX]

[DOI]

CoRR, 2019

Provably robust boosted decision stumps and trees against adversarial attacks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Spectral Clustering of Signed Graphs via Matrix Power Means.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

On the loss landscape of a class of deep neural networks with no bad local valleys.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

Proceedings of the 7th International Conference on Learning Representations, 2019

Sparse and Imperceivable Adversarial Attacks.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Disentangling Adversarial Robustness and Generalization.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Provable Robustness of ReLU networks via Maximization of Linear Regions.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Community Detection in Networks via Nonlinear Modularity Eigenvectors.

[BibT_eX]

[DOI]

SIAM J. Appl. Math., 2018

Analysis and Optimization of Loss Functions for Multiclass, Top-k, and Multilabel Classification.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Logit Pairing Methods Can Fool Gradient-Based Attacks.

[BibT_eX]

[DOI]

Marius Mosbach

Thomas Alexander Trost

Dietrich Klakow

CoRR, 2018

A unifying Perron-Frobenius theorem for nonnegative tensors via multi-homogeneous maps.

[BibT_eX]

[DOI]

CoRR, 2018

Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

Proceedings of the 35th International Conference on Machine Learning, 2018

Optimization Landscape and Expressivity of Deep CNNs.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

The loss surface and expressivity of deep convolutional neural networks.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

A Randomized Gradient-Free Attack on ReLU Networks.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 40th German Conference, 2018

The Power Mean Laplacian for Multilayer Graph Clustering.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

An Efficient Multilinear Optimization Framework for Hypergraph Matching.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

The Loss Surface of Deep and Wide Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Variants of RMSProp and Adagrad with Logarithmic Regret Bounds.

[BibT_eX]

[DOI]

Mahesh Chandra Mukkamala

Proceedings of the 34th International Conference on Machine Learning, 2017

Simple Does It: Weakly Supervised Instance and Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Nodal domain theorem for the graph p-Laplacian.

[BibT_eX]

[DOI]

CoRR, 2016

Weakly Supervised Semantic Labelling and Instance Segmentation.

[BibT_eX]

[DOI]

CoRR, 2016

Clustering Signed Networks with the Geometric Mean of Laplacians.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Improved Image Boundaries for Better Video Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Latent Embeddings for Zero-Shot Classification.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Loss Functions for Top-k Error: Analysis and Insights.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Weakly Supervised Object Boundaries.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Correction of noisy labels via mutual consistency check.

[BibT_eX]

[DOI]

Sahely Bhadra

Neurocomputing, 2015

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361).

[BibT_eX]

[DOI]

Gábor Lugosi

Lorenzo Rosasco

Dagstuhl Reports, 2015

Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices.

[BibT_eX]

[DOI]

Martin Slawski

Ping Li

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Top-k Multiclass SVM.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Efficient Output Kernel Learning for Multiple Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A flexible tensor block coordinate ascent scheme for hypergraph matching.

[BibT_eX]

[DOI]

Quynh Nguyen Ngoc

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Classifier based graph construction for video segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Learning using privileged information: SV M+ and weighted SVM.

[BibT_eX]

[DOI]

Neural Networks, 2014

Hitting and commute times in large random neighborhood graphs.

[BibT_eX]

[DOI]

Agnes Radl

J. Mach. Learn. Res., 2014

Tight Continuous Relaxation of the Balanced k-Cut Problem.

[BibT_eX]

[DOI]

Pramod Kaushik Mudrakarta

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Robust PCA: Optimization of the Robust Reconstruction Error Over the Stiefel Manifold.

[BibT_eX]

[DOI]

Anastasia Podosinnikova

Proceedings of the Pattern Recognition - 36th German Conference, 2014

Learning Must-Link Constraints for Video Segmentation Based on Spectral Clustering.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 36th German Conference, 2014

Scalable Multitask Representation Learning for Scene Classification.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Learning Using Privileged Information: SVM+ and Weighted SVM.

[BibT_eX]

[DOI]

CoRR, 2013

Nonlinear Eigenproblems in Data Analysis - Balanced Graph Cuts and the RatioDCA-Prox.

[BibT_eX]

[DOI]

Leonardo Jost

CoRR, 2013

Towards realistic team formation in social networks based on densest subgraphs.

[BibT_eX]

[DOI]

Proceedings of the 22nd International World Wide Web Conference, 2013

Matrix factorization with binary components.

[BibT_eX]

[DOI]

Martin Slawski

Pavlo Lutsik

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited.

[BibT_eX]

[DOI]

Leonardo Jost

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Constrained fractional set programs and their application in local clustering and community detection.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Constrained 1-Spectral Clustering.

[BibT_eX]

[DOI]

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Isotope pattern deconvolution for peptide mass spectrometry by non-negative least squares/least absolute deviation template matching.

[BibT_eX]

[DOI]

BMC Bioinform., 2012

2011

Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291).

[BibT_eX]

[DOI]

Dagstuhl Reports, 2011

How the result of graph clustering methods depends on the construction of the graph

[BibT_eX]

[DOI]

CoRR, 2011

Sparse recovery by thresholded non-negative least squares.

[BibT_eX]

[DOI]

Martin Slawski

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Nonparametric Regression between General Riemannian Manifolds.

[BibT_eX]

[DOI]

Florian Steinke

Bernhard Schölkopf

SIAM J. Imaging Sci., 2010

Hitting times, commute distances and the spectral gap for large random geometric graphs

[BibT_eX]

[DOI]

Agnes Radl

CoRR, 2010

Getting lost in space: Large sample analysis of the resistance distance.

[BibT_eX]

[DOI]

Agnes Radl

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009

Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2009

Large-scale antibody profiling of human blood sera: The future of molecular diagnosis.

[BibT_eX]

[DOI]

Inform. Spektrum, 2009

Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction.

[BibT_eX]

[DOI]

Kwang In Kim

Florian Steinke

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Robust Nonparametric Regression with Metric-Space Valued Output.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Spectral clustering based on the graph p-Laplacian.

[BibT_eX]

[DOI]

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

Manifold-valued Thin-Plate Splines with Applications in Computer Graphics.

[BibT_eX]

[DOI]

Comput. Graph. Forum, 2008

Enhancement of Bright Video Features for HDR Displays.

[BibT_eX]

[DOI]

Comput. Graph. Forum, 2008

Non-parametric Regression Between Manifolds.

[BibT_eX]

[DOI]

Florian Steinke

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Influence of graph construction on graph-based clustering measures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Graph Laplacians and their Convergence on Random Neighborhood Graphs.

[BibT_eX]

[DOI]

Jean-Yves Audibert

J. Mach. Learn. Res., 2007

Cluster Identification in Nearest-Neighbor Graphs.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

Manifold Denoising as Preprocessing for Finding Natural Representations of Data.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006

Manifold Denoising.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Uniform Convergence of Adaptive Graph-Based Regularization.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005

Geometrical aspects of statistical learning theory.

[BibT_eX]

[DOI]

PhD thesis, 2005

Maximal margin classification for metric spaces.

[BibT_eX]

[DOI]

Bernhard Schölkopf

J. Comput. Syst. Sci., 2005

Intrinsic dimensionality estimation of submanifolds in Rd.

[BibT_eX]

[DOI]

Jean-Yves Audibert

Proceedings of the Machine Learning, 2005

From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians.

[BibT_eX]

[DOI]

Jean-Yves Audibert

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

Hilbertian Metrics and Positive Definite Kernels on Probability Measures.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Hilbertian Metrics on Probability Measures and Their Application in SVM?s.

[BibT_eX]

[DOI]

Thomas Navin Lal

Proceedings of the Pattern Recognition, 26th DAGM Symposium, August 30, 2004

2003

Measure Based Regularization.

[BibT_eX]

[DOI]

Olivier Chapelle

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Maximal Margin Classification for Metric Spaces.

[BibT_eX]

[DOI]