Benjamin D. Haeffele

52 papers A* 10A 1Journal 30Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Adaptive Stain Normalization for Cross-Domain Medical Histology. MICCAI (7) Tianyue Xu, Yanlin Wu, Abhai K. Tripathi, Matthew M. Ippolito, Benjamin D. Haeffele
2025	J	`jnl`	Adaptive Stain Normalization for Cross-Domain Medical Histology. CoRR Tianyue Xu, Yanlin Wu, Abhai K. Tripathi, Matthew M. Ippolito, Benjamin D. Haeffele
2025	J	`jnl`	An Overview of Low-Rank Structures in the Training and Adaptation of Large Models. CoRR Laura Balzano, Tianjiao Ding, Benjamin D. Haeffele, Soo Min Kwon, Qing Qu, Peng Wang, Zhangyang Wang, Can Yaras
2025	—	`conf`	Nonconvex Linear System Identification with Minimal State Representation. L4DC Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar M. Ziemann, René Vidal
2025	J	`jnl`	Nonconvex Linear System Identification with Minimal State Representation. CoRR Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, Ingvar M. Ziemann, René Vidal
2024	J	`jnl`	A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks. CoRR Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg, René Vidal
2024	J	`jnl`	Token Statistics Transformer: Linear-Time Attention via Variational Rate Reduction. CoRR Ziyang Wu, Tianjiao Ding, Yifu Lu, Druv Pai, Jingyuan Zhang, Weida Wang, Yaodong Yu, Yi Ma, Benjamin D. Haeffele
2024	—	`conf`	Vertex Proportion Loss for Multi-class Cell Detection from Label Proportions. MICCAI (12) Carolina Pacheco, Florence Yellin, René Vidal, Benjamin D. Haeffele
2024	J	`jnl`	Wave Physics-Informed Matrix Factorizations. IEEE Trans. Signal Process. Harsha Vardhan Tetali, Joel B. Harley, Benjamin D. Haeffele
2024	J	`jnl`	White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? J. Mach. Learn. Res. Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma
2023	J	`jnl`	Interpretable by Design: Learning Predictors by Composing Interpretable Queries. IEEE Trans. Pattern Anal. Mach. Intell. Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman
2023	J	`jnl`	Lens Free Holographic Imaging for Urinary Tract Infection Screening. IEEE Trans. Biomed. Eng. Gregory N. McKay, Anisha Oommen, Carolina Pacheco, Mason T. Chen, Stuart C. Ray, René Vidal, Benjamin D. Haeffele, Nicholas J. Durr
2023	A*	`conf`	Unsupervised Manifold Linearizing and Clustering. ICCV Tianjiao Ding, Shengbang Tong, Kwan Ho Ryan Chan, Xili Dai, Yi Ma, Benjamin D. Haeffele
2023	J	`jnl`	Unsupervised Manifold Linearizing and Clustering. CoRR Tianjiao Ding, Shengbang Tong, Kwan Ho Ryan Chan, Xili Dai, Yi Ma, Benjamin D. Haeffele
2023	J	`jnl`	Variational Information Pursuit for Interpretable Predictions. CoRR Aditya Chattopadhyay, Kwan Ho Ryan Chan, Benjamin D. Haeffele, Donald Geman, René Vidal
2023	J	`jnl`	Wave Physics-informed Matrix Factorizations. CoRR Harsha Vardhan Tetali, Joel B. Harley, Benjamin D. Haeffele
2023	A*	`conf`	White-Box Transformers via Sparse Rate Reduction. NeurIPS Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma
2023	J	`jnl`	White-Box Transformers via Sparse Rate Reduction. CoRR Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin D. Haeffele, Yi Ma
2023	J	`jnl`	White-Box Transformers via Sparse Rate Reduction: Compression Is All There Is? CoRR Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Hao Bai, Yuexiang Zhai, Benjamin D. Haeffele, Yi Ma
2022	A*	`conf`	Efficient Maximal Coding Rate Reduction by Variational Forms. CVPR Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele
2022	J	`jnl`	Efficient Maximal Coding Rate Reduction by Variational Forms. CoRR Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele
2022	J	`jnl`	Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension. CoRR Paris V. Giampouras, Benjamin D. Haeffele, René Vidal
2022	J	`jnl`	Interpretable by Design: Learning Predictors by Composing Interpretable Queries. CoRR Aditya Chattopadhyay, Stewart Slocum, Benjamin D. Haeffele, René Vidal, Donald Geman
2022	J	`jnl`	Learning Globally Smooth Functions on Manifolds. CoRR Juan Cerviño, Luiz F. O. Chamon, Benjamin D. Haeffele, René Vidal, Alejandro Ribeiro
2022	A*	`conf`	Understanding Doubly Stochastic Clustering. ICML Tianjiao Ding, Derek Lim, René Vidal, Benjamin D. Haeffele
2022	—	`conf`	Unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction. DDDAS Joel B. Harley, Benjamin D. Haeffele, Harsha Vardhan Tetali
2021	A*	`conf`	Understanding the Dynamics of Gradient Flow in Overparameterized Linear models. ICML Salma Tarmoun, Guilherme França, Benjamin D. Haeffele, René Vidal
2021	J	`jnl`	Wave-Informed Matrix Factorization withGlobal Optimality Guarantees. CoRR Harsha Vardhan Tetali, Joel B. Harley, Benjamin D. Haeffele
2020	J	`jnl`	A Critique of Self-Expressive Deep Subspace Clustering. CoRR Benjamin D. Haeffele, Chong You, René Vidal
2020	A*	`conf`	A novel variational form of the Schatten-$p$ quasi-norm. NeurIPS Paris Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele
2020	J	`jnl`	A novel variational form of the Schatten-p quasi-norm. CoRR Paris Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele
2020	J	`jnl`	Doubly Stochastic Subspace Clustering. CoRR Derek Lim, René Vidal, Benjamin D. Haeffele
2020	A*	`conf`	On the Regularization Properties of Structured Dropout. CVPR Ambar Pal, Connor Lane, René Vidal, Benjamin D. Haeffele
2020	J	`jnl`	Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications. IEEE Trans. Pattern Anal. Mach. Intell. Benjamin D. Haeffele, René Vidal
2019	—	`conf`	Adaptive Online k-Subspaces with Cooperative Re-Initialization. ICCV Workshops Connor Lane, Benjamin D. Haeffele, René Vidal
2019	—	`conf`	An Optical Model of Whole Blood for Detecting Platelets in Lens-Free Images. SASHIMI@MICCAI Benjamin D. Haeffele, Christian Pick, Ziduo Lin, Evelien Mathieu, Stuart C. Ray, René Vidal
2019	—	`conf`	Classifying and Comparing Approaches to Subspace Clustering with Missing Data. ICCV Workshops Connor Lane, Ron Boger, Chong You, Manolis C. Tsakiris, Benjamin D. Haeffele, René Vidal
2019	J	`jnl`	Global Optimality in Separable Dictionary Learning with Applications to the Analysis of Diffusion MRI. SIAM J. Imaging Sci. Evan Schwab, Benjamin D. Haeffele, René Vidal, Nicolas Charon
2019	—	`conf`	Joint Holographic Detection and Reconstruction. MLMI@MICCAI Florence Yellin, Benjamín Béjar Haro, Benjamin D. Haeffele, Evelien Mathieu, Christian Pick, Stuart C. Ray, René Vidal
2019	J	`jnl`	On the Regularization Properties of Structured Dropout. CoRR Ambar Pal, Connor Lane, René Vidal, Benjamin D. Haeffele
2018	A	`conf`	Dropout as a Low-Rank Regularizer for Matrix Factorization. AISTATS Jacopo Cavazza, Pietro Morerio, Benjamin D. Haeffele, Connor Lane, Vittorio Murino, René Vidal
2018	A*	`conf`	Multi-Cell Detection and Classification Using a Generative Convolutional Model. CVPR Florence Yellin, Benjamin D. Haeffele, Sophie Roth, René Vidal
2018	J	`jnl`	Separable Dictionary Learning with Global Optimality and Applications to Diffusion MRI. CoRR Evan Schwab, Benjamin D. Haeffele, Nicolas Charon, René Vidal
2017	J	`jnl`	An Analysis of Dropout for Matrix Factorization. CoRR Jacopo Cavazza, Connor Lane, Benjamin D. Haeffele, Vittorio Murino, René Vidal
2017	—	`conf`	Blood cell detection and counting in holographic lens-free imaging by convolutional sparse dictionary learning and coding. ISBI Florence Yellin, Benjamin D. Haeffele, René Vidal
2017	J	`jnl`	Dropout as a Low-Rank Regularizer for Matrix Factorization. CoRR Jacopo Cavazza, Pietro Morerio, Benjamin D. Haeffele, Connor Lane, Vittorio Murino, René Vidal
2017	—	`conf`	Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery. MICCAI (2) Benjamin D. Haeffele, Richard Stahl, Geert Vanmeerbeeck, René Vidal
2017	A*	`conf`	Global Optimality in Neural Network Training. CVPR Benjamin D. Haeffele, René Vidal
2017	—	`conf`	Removal of the twin image artifact in holographic lens-free imaging by sparse dictionary learning and coding. ISBI Benjamin D. Haeffele, Sophie Roth, Lin Zhou, René Vidal
2017	J	`jnl`	Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications. CoRR Benjamin D. Haeffele, René Vidal
2015	J	`jnl`	Global Optimality in Tensor Factorization, Deep Learning, and Beyond. CoRR Benjamin D. Haeffele, René Vidal
2014	A*	`conf`	Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing. ICML Benjamin D. Haeffele, Eric Young, René Vidal