Benjamin D. Haeffele

Orcid: 0000-0002-7544-7347

According to our database1, Benjamin D. Haeffele authored at least 38 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Vertex Proportion Loss for Multi-class Cell Detection from Label Proportions.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Performance Bounds for Active Binary Testing with Information Maximization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Interpretable by Design: Learning Predictors by Composing Interpretable Queries.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Lens Free Holographic Imaging for Urinary Tract Infection Screening.
IEEE Trans. Biomed. Eng., March, 2023

Wave Physics-informed Matrix Factorizations.
CoRR, 2023

White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is?
CoRR, 2023

Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions.
CoRR, 2023

White-Box Transformers via Sparse Rate Reduction.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Globally Smooth Functions on Manifolds.
Proceedings of the International Conference on Machine Learning, 2023

Variational Information Pursuit for Interpretable Predictions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unsupervised Manifold Linearizing and Clustering.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Understanding Doubly Stochastic Clustering.
Proceedings of the International Conference on Machine Learning, 2022

Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction.
Proceedings of the Dynamic Data Driven Applications Systems - 4th International Conference, 2022

Efficient Maximal Coding Rate Reduction by Variational Forms.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Wave-Informed Matrix Factorization withGlobal Optimality Guarantees.
CoRR, 2021

Understanding the Dynamics of Gradient Flow in Overparameterized Linear models.
Proceedings of the 38th International Conference on Machine Learning, 2021

A Critique of Self-Expressive Deep Subspace Clustering.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Doubly Stochastic Subspace Clustering.
CoRR, 2020

A novel variational form of the Schatten-$p$ quasi-norm.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Regularization Properties of Structured Dropout.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Global Optimality in Separable Dictionary Learning with Applications to the Analysis of Diffusion MRI.
SIAM J. Imaging Sci., 2019

Joint Holographic Detection and Reconstruction.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

An Optical Model of Whole Blood for Detecting Platelets in Lens-Free Images.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2019

Adaptive Online k-Subspaces with Cooperative Re-Initialization.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

Classifying and Comparing Approaches to Subspace Clustering with Missing Data.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Separable Dictionary Learning with Global Optimality and Applications to Diffusion MRI.
CoRR, 2018

Multi-Cell Detection and Classification Using a Generative Convolutional Model.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Dropout as a Low-Rank Regularizer for Matrix Factorization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
An Analysis of Dropout for Matrix Factorization.
CoRR, 2017

Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Blood cell detection and counting in holographic lens-free imaging by convolutional sparse dictionary learning and coding.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Removal of the twin image artifact in holographic lens-free imaging by sparse dictionary learning and coding.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Global Optimality in Neural Network Training.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2015
Global Optimality in Tensor Factorization, Deep Learning, and Beyond.
CoRR, 2015

2014
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing.
Proceedings of the 31th International Conference on Machine Learning, 2014


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