Blaschko, Matthew B.

49 publications

ICML 2025 A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators Han Zhou, Jordy Van Landeghem, Teodora Popordanoska, Matthew B. Blaschko

WACV 2025 AC-IND: Sparse CT Reconstruction Based on Attenuation Coefficient Estimation and Implicit Neural Distribution Wangduo Xie, Richard Schoonhoven, Tristan van Leeuwen, Matthew B. Blaschko

NeurIPS 2025 Balancing Multimodal Training Through Game-Theoretic Regularization Konstantinos Kontras, Thomas Strypsteen, Christos Chatzichristos, Paul Pu Liang, Matthew B. Blaschko, Maarten De Vos

UAI 2025 Bayesian Optimization over Bounded Domains with the Beta Product Kernel Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin

NeurIPS 2025 DAVE: Diagnostic Benchmark for Audio Visual Evaluation Gorjan Radevski, Teodora Popordanoska, Matthew B. Blaschko, Tinne Tuytelaars

TMLR 2025 Diversity-Driven View Subset Selection for Indoor Novel View Synthesis Zehao Wang, Han Zhou, Matthew B. Blaschko, Tinne Tuytelaars, Minye Wu

TMLR 2025 Jigsaw-R1: A Study of Rule-Based Visual Reinforcement Learning with Jigsaw Puzzles Zifu Wang, Junyi Zhu, Bo Tang, Zhiyu Li, Feiyu Xiong, Jiaqian Yu, Matthew B. Blaschko

ICLR 2025 Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

NeurIPSW 2024 Bayesian Optimization over Bounded Domains with Beta Product Kernels Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin

WACV 2024 Beyond Classification: Definition and Density-Based Estimation of Calibration in Object Detection Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko

NeurIPS 2024 Can LLMs Learn by Teaching for Better Reasoning? a Preliminary Study Xuefei Ning, Zifu Wang, Shiyao Li, Zinan Lin, Peiran Yao, Tianyu Fu, Matthew B. Blaschko, Guohao Dai, Huazhong Yang, Yu Wang

AISTATS 2024 Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors Teodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin, Florian Buettner, Matthew B. Blaschko

TMLR 2024 Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction Jiayang Shi, Junyi Zhu, Daniel Pelt, Joost Batenburg, Matthew B. Blaschko

NeurIPS 2024 LaSCal: Label-Shift Calibration Without Target Labels Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko

MIDL 2024 Laparoflow-SSL: Image Analysis from a Tiny Dataset Through Self-Supervised Transformers Leveraging Unlabeled Surgical Video Karel Moens, Jonas De Vylder, Matthew B. Blaschko, Tinne Tuytelaars

NeurIPS 2024 Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation? Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Saikat Roy, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Klaus H. Maier-Hein, Paul Jaeger, Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, Yong Xia, Zhaohu Xing, Lei Zhu, Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad, Dorit Merhof, Pengcheng Shi, Ting Ma, Yuxin Du, Fan Bai, Tiejun Huang, Bo Zhao, Haonan Wang, Xiaomeng Li, Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej A. Mazurowski, Saumya Gupta, Linshan Wu, Jiaxin Zhuang, Hao Chen, Holger Roth, Daguang Xu, Matthew B. Blaschko, Sergio Decherchi, Andrea Cavalli, Alan L. Yuille, Zongwei Zhou

ACML 2023 A Corrected Expected Improvement Acquisition Function Under Noisy Observations Han Zhou, Xingchen Ma, Matthew B Blaschko

CVPR 2023 Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization Junyi Zhu, Xingchen Ma, Matthew B. Blaschko

TMLR 2023 Improving Differentially Private SGD via Randomly Sparsified Gradients Junyi Zhu, Matthew B. Blaschko

ICML 2023 Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning Junyi Zhu, Ruicong Yao, Matthew B. Blaschko

TMLR 2022 Greedy Bayesian Posterior Approximation with Deep Ensembles Aleksei Tiulpin, Matthew B. Blaschko

ECML-PKDD 2022 MRF-UNets: Searching UNet with Markov Random Fields Zifu Wang, Matthew B. Blaschko

AAAI 2022 Predicting Physical World Destinations for Commands Given to Self-Driving Cars Dusan Grujicic, Thierry Deruyttere, Marie-Francine Moens, Matthew B. Blaschko

NeurIPSW 2022 Tackling Personalized Federated Learning with Label Concept Drift via Hierarchical Bayesian Modeling Xingchen Ma, Junyi Zhu, Matthew B. Blaschko

ICML 2021 Meta-Cal: Well-Controlled Post-Hoc Calibration by Ranking Xingchen Ma, Matthew B. Blaschko

ICLR 2021 R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu, Matthew B. Blaschko

ECCVW 2020 Commands 4 Autonomous Vehicles (C4AV) Workshop Summary Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew B. Blaschko, Tinne Tuytelaars, Marie-Francine Moens

ICCVW 2019 Function Norms for Neural Networks Amal Rannen-Triki, Maxim Berman, Vladimir Kolmogorov, Matthew B. Blaschko

ICCV 2017 Encoder Based Lifelong Learning Amal Rannen, Rahaf Aljundi, Matthew B. Blaschko, Tinne Tuytelaars

ICLR 2017 Joint Embeddings of Scene Graphs and Images Eugene Belilovsky, Matthew B. Blaschko, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel

ICML 2017 Learning to Discover Sparse Graphical Models Eugene Belilovsky, Kyle Kastner, Gael Varoquaux, Matthew B. Blaschko

ICLR 2017 Learning to Discover Sparse Graphical Models Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko

AISTATS 2016 A Convex Surrogate Operator for General Non-Modular Loss Functions Jiaqian Yu, Matthew B. Blaschko

ICLR 2016 A Test of Relative Similarity for Model Selection in Generative Models Wacha Bounliphone, Eugene Belilovsky, Matthew B. Blaschko, Ioannis Antonoglou, Arthur Gretton

WACV 2016 Discriminative Training of CRF Models with Probably Submodular Constraints Wojciech Zaremba, Matthew B. Blaschko

NeurIPS 2016 Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity Eugene Belilovsky, Gaël Varoquaux, Matthew B Blaschko

MLJ 2015 Convex Relaxations of Penalties for Sparse Correlated Variables with Bounded Total Variation Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux, Matthew B. Blaschko

CVPR 2014 Understanding Objects in Detail with Fine-Grained Attributes Andrea Vedaldi, Siddharth Mahendran, Stavros Tsogkas, Subhransu Maji, Ross Girshick, Juho Kannala, Esa Rahtu, Iasonas Kokkinos, Matthew B. Blaschko, David Weiss, Ben Taskar, Karen Simonyan, Naomi Saphra, Sammy Mohamed

ECML-PKDD 2013 Taxonomic Prediction with Tree-Structured Covariances Matthew B. Blaschko, Wojciech Zaremba, Arthur Gretton

ECCV 2012 Taxonomic Multi-Class Prediction and Person Layout Using Efficient Structured Ranking Arpit Mittal, Matthew B. Blaschko, Andrew Zisserman, Philip H. S. Torr

ICCV 2011 Learning Equivariant Structured Output SVM Regressors Andrea Vedaldi, Matthew B. Blaschko, Andrew Zisserman

ICCV 2011 Learning a Category Independent Object Detection Cascade Esa Rahtu, Juho Kannala, Matthew B. Blaschko

MLJ 2009 Structured Prediction by Joint Kernel Support Estimation Christoph H. Lampert, Matthew B. Blaschko

CVPR 2008 Beyond Sliding Windows: Object Localization by Efficient Subwindow Search Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann

CVPR 2008 Correlational Spectral Clustering Matthew B. Blaschko, Christoph H. Lampert

ECCV 2008 Learning to Localize Objects with Structured Output Regression Matthew B. Blaschko, Christoph H. Lampert

ECML-PKDD 2008 Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton

CVPR 2005 Combining Local and Global Image Features for Object Class Recognition Dimitri A. Lisin, Marwan A. Mattar, Matthew B. Blaschko, Erik G. Learned-Miller, Mark C. Benfield

CVPRW 2005 Combining Local and Global Image Features for Object Class Recognition Dimitri A. Lisin, Marwan A. Mattar, Matthew B. Blaschko, Erik G. Learned-Miller, Mark C. Benfield