Matthew B. Blaschko

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

R-GAP: Recursive Gradient Attack on Privacy.

[BibT_eX]

[DOI]

Junyi Zhu

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading From Plain Radiographs.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2020

Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2020

The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2020

Discriminative Training of Conditional Random Fields with Probably Submodular Constraints.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2020

Commands 4 Autonomous Vehicles (C4AV) Workshop Summary.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

AOWS: Adaptive and Optimal Network Width Search With Latency Constraints.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning to ground medical text in a 3D human atlas.

[BibT_eX]

[DOI]

Proceedings of the 24th Conference on Computational Natural Language Learning, 2020

Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization.

[BibT_eX]

[DOI]

Xingchen Ma

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Scattering Networks for Hybrid Representation Learning.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice.

[BibT_eX]

[DOI]

CoRR, 2019

Generating superpixels using deep image representations.

[BibT_eX]

[DOI]

Thomas Verelst

CoRR, 2019

Artery-vein segmentation in fundus images using a fully convolutional network.

[BibT_eX]

[DOI]

Comput. Medical Imaging Graph., 2019

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Function Norms for Neural Networks.

[BibT_eX]

[DOI]

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

A Bayesian Optimization Framework for Neural Network Compression.

[BibT_eX]

[DOI]

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

Designing MacPherson Suspension Architectures Using Bayesian Optimization.

[BibT_eX]

[DOI]

Friedrich Wolf-Monheim

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Adaptive Compression-based Lifelong Learning.

[BibT_eX]

[DOI]

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

Yes, IoU loss is submodular - as a function of the mispredictions.

[BibT_eX]

[DOI]

CoRR, 2018

Supermodular Locality Sensitive Hashes.

[BibT_eX]

[DOI]

CoRR, 2018

Efficient semantic image segmentation with superpixel pooling.

[BibT_eX]

[DOI]

Mathijs Schuurmans

CoRR, 2018

An ensemble deep learning based approach for red lesion detection in fundus images.

[BibT_eX]

[DOI]

Comput. Methods Programs Biomed., 2018

Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks.

[BibT_eX]

[DOI]

Comput. Medical Imaging Graph., 2018

Towards a Glaucoma Risk Index Based on Simulated Hemodynamics from Fundus Images.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Shallow and Deep Models for Domain Adaptation problems.

[BibT_eX]

[DOI]

Siamak Mehrkanoon

Johan A. K. Suykens

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks.

[BibT_eX]

[DOI]

Amal Rannen Triki

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.

[BibT_eX]

[DOI]

José Ignacio Orlando

Elena Prokofyeva

IEEE Trans. Biomed. Eng., 2017

Stochastic Weighted Function Norm Regularization.

[BibT_eX]

[DOI]

Amal Rannen Triki

CoRR, 2017

An Efficient Decomposition Framework for Discriminative Segmentation with Supermodular Losses.

[BibT_eX]

[DOI]

CoRR, 2017

Learning to Detect Red Lesions in Fundus Photographs: An Ensemble Approach based on Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2017

Optimization of the Jaccard index for image segmentation with the Lovász hinge.

[BibT_eX]

[DOI]

CoRR, 2017

Learning to Discover Sparse Graphical Models.

[BibT_eX]

[DOI]

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

Joint Embeddings of Scene Graphs and Images.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Encoder Based Lifelong Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

Slack and Margin Rescaling as Convex Extensions of Supermodular Functions.

[BibT_eX]

[DOI]

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2017

2016

Discovering predictors of mental health service utilization with k-support regularized logistic regression.

[BibT_eX]

[DOI]

Hakim Sidahmed

Elena Prokofyeva

Inf. Sci., 2016

The pyramid quantized Weisfeiler-Lehman graph representation.

[BibT_eX]

[DOI]

Katerina Gkirtzou

Neurocomputing, 2016

Stochastic Function Norm Regularization of Deep Networks.

[BibT_eX]

[DOI]

Amal Rannen Triki

CoRR, 2016

Fast Non-Parametric Tests of Relative Dependency and Similarity.

[BibT_eX]

[DOI]

CoRR, 2016

A Test of Relative Similarity For Model Selection in Generative Models.

[BibT_eX]

[DOI]

Proceedings of the 4th International Conference on Learning Representations, 2016

Discriminative training of CRF models with probably submodular constraints.

[BibT_eX]

[DOI]

Wojciech Zaremba

Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity.

[BibT_eX]

[DOI]

Eugene Belilovsky

Gaël Varoquaux

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

Efficient, dense, object-based segmentation from RGBD video.

[BibT_eX]

[DOI]

Mahsa Ghafarianzadeh

Gabe Sibley

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Efficient Learning for Discriminative Segmentation with Supermodular Losses.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference 2016, 2016

A Convex Surrogate Operator for General Non-Modular Loss Functions.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Convex relaxations of penalties for sparse correlated variables with bounded total variation.

[BibT_eX]

[DOI]

Mach. Learn., 2015

The Lovász Hinge: A Convex Surrogate for Submodular Losses.

[BibT_eX]

[DOI]

CoRR, 2015

Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm.

[BibT_eX]

[DOI]

Comput. Medical Imaging Graph., 2015

Learning Submodular Losses with the Lovasz Hinge.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

A low variance consistent test of relative dependency.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

A low variance consistent test of relative dependency.

[BibT_eX]

[DOI]

Wacha Bounliphone

Arthur Gretton

CoRR, 2014

Learning Fully-Connected CRFs for Blood Vessel Segmentation in Retinal Images.

[BibT_eX]

[DOI]

José Ignacio Orlando

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

An <i>O</i>(n \log n) Cutting Plane Algorithm for Structured Output Ranking.

[BibT_eX]

[DOI]

Arpit Mittal

Esa Rahtu

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

Understanding Objects in Detail with Fine-Grained Attributes.

[BibT_eX]

[DOI]

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

Unsupervised Spatio-Temporal Segmentation with Sparse Spectral-Clustering.

[BibT_eX]

[DOI]

Mahsa Ghafarianzadeh

Gabe Sibley

Proceedings of the British Machine Vision Conference, 2014

2013

A Note on k-support Norm Regularized Risk Minimization

[BibT_eX]

[DOI]

CoRR, 2013

Fine-Grained Visual Classification of Aircraft.

[BibT_eX]

[DOI]

CoRR, 2013

Non Maximal Suppression in Cascaded Ranking Models.

[BibT_eX]

[DOI]

Juho Kannala

Esa Rahtu

Proceedings of the Image Analysis, 18th Scandinavian Conference, 2013

Taxonomic Prediction with Tree-Structured Covariances.

[BibT_eX]

[DOI]

Wojciech Zaremba

Arthur Gretton

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

B-test: A Non-parametric, Low Variance Kernel Two-sample Test.

[BibT_eX]

[DOI]

Wojciech Zaremba

Arthur Gretton

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

fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning in Medical Imaging - 4th International Workshop, 2013

Sparse Classification with MRI Based Markers for Neuromuscular Disease Categorization.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning in Medical Imaging - 4th International Workshop, 2013

FMRI analysis of cocaine addiction using k-support sparsity.

[BibT_eX]

[DOI]

Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013

Learning from M/EEG Data with Variable Brain Activation Delays.

[BibT_eX]

[DOI]

Proceedings of the Information Processing in Medical Imaging, 2013

2012

Guest Editorial: Special Issue on Structured Prediction and Inference.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2012

Perceptron Learning of SAT.

[BibT_eX]

[DOI]

Alex Flint

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Taxonomic Multi-class Prediction and Person Layout Using Efficient Structured Ranking.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2012, 2012

2011

Semi-supervised kernel canonical correlation analysis with application to human fMRI.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2011

Learning equivariant structured output SVM regressors.

[BibT_eX]

[DOI]

Andrea Vedaldi

Andrew Zisserman

Proceedings of the IEEE International Conference on Computer Vision, 2011

Learning a category independent object detection cascade.

[BibT_eX]

[DOI]

Esa Rahtu

Juho Kannala

Proceedings of the IEEE International Conference on Computer Vision, 2011

Branch and Bound Strategies for Non-maximal Suppression in Object Detection.

[BibT_eX]

[DOI]

Proceedings of the Energy Minimazation Methods in Computer Vision and Pattern Recognition, 2011

2010

Unsupervised Object Discovery: A Comparison.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2010

Simultaneous Object Detection and Ranking with Weak Supervision.

[BibT_eX]

[DOI]

Andrea Vedaldi

Andrew Zisserman

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

Kernel methods in computer vision: object localization, clustering, and taxonomy discovery.

[BibT_eX]

[DOI]

Matthew Brian Blaschko

PhD thesis, 2009

Efficient Subwindow Search: A Branch and Bound Framework for Object Localization.

[BibT_eX]

[DOI]

Thomas Hofmann

IEEE Trans. Pattern Anal. Mach. Intell., 2009

Structured prediction by joint kernel support estimation.

[BibT_eX]

[DOI]

Mach. Learn., 2009

Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity.

[BibT_eX]

[DOI]

Jacquelyn A. Shelton

Andreas M. Bartels

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

Object Localization with Global and Local Context Kernels.

[BibT_eX]

[DOI]

Proceedings of the British Machine Vision Conference, 2009

2008

Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis.

[BibT_eX]

[DOI]