Matthew B. Blaschko

220 papers A* 30A 14B 4C 3Journal 125Unranked 44

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	NAB: Neural Adaptive Binning for Sparse-View CT reconstruction. CoRR Wangduo Xie, Matthew B. Blaschko
2026	J	`jnl`	Self-Balancing Multimodal Models via Multi-Loss Gradient Modulation. Int. J. Comput. Vis. Konstantinos Kontras, Christos Chatzichristos, Matthew B. Blaschko, Maarten De Vos
2026	J	`jnl`	Spectrum Matching: a Unified Perspective for Superior Diffusability in Latent Diffusion. CoRR Mang Ning, Mingxiao Li, Le Zhang, Lanmiao Liu, Matthew B. Blaschko, Albert Ali Salah, Itir Önal Ertugrul
2025	A*	`conf`	A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators. ICML Han Zhou, Jordy Van Landeghem, Teodora Popordanoska, Matthew B. Blaschko
2025	A	`conf`	AC-IND: Sparse CT Reconstruction Based on Attenuation Coefficient Estimation and Implicit Neural Distribution. WACV Wangduo Xie, Richard Schoonhoven, Tristan van Leeuwen, Matthew B. Blaschko
2025	A	`conf`	Bayesian Optimization over Bounded Domains with the Beta Product Kernel. UAI Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin
2025	J	`jnl`	Bayesian Optimization over Bounded Domains with the Beta Product Kernel. CoRR Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko, Aleksei Tiulpin
2025	J	`jnl`	Beyond Segmentation: Confidence-Aware and Debiased Estimation of Ratio-based Biomarkers. CoRR Jiameng Li, Teodora Popordanoska, Sebastian G. Gruber, Frederik Maes, Matthew B. Blaschko
2025	A	`conf`	CCMPlus: Leveraging Latent Causal Relationships Among Web Services for Traffic Prediction. ECAI Chang Tian, Mingzhe Xing, Zenglin Shi, Matthew B. Blaschko, Yinliang Yue, Marie-Francine Moens
2025	J	`jnl`	CLASH: A Benchmark for Cross-Modal Contradiction Detection. CoRR Teodora Popordanoska, Jiameng Li, Matthew B. Blaschko
2025	J	`jnl`	ChromaFormer: A Scalable and Accurate Transformer Architecture for Land Cover Classification. CoRR Mingshi Li, Dusan Grujicic, Ben Somers, Stien Heremans, Steven De Saeger, Matthew B. Blaschko
2025	J	`jnl`	DAVE: Diagnostic benchmark for Audio Visual Evaluation. CoRR Gorjan Radevski, Teodora Popordanoska, Matthew B. Blaschko, Tinne Tuytelaars
2025	J	`jnl`	Diversity-Driven View Subset Selection for Indoor Novel View Synthesis. Trans. Mach. Learn. Res. Zehao Wang, Han Zhou, Matthew B. Blaschko, Tinne Tuytelaars, Minye Wu
2025	J	`jnl`	Jigsaw-R1: A Study of Rule-based Visual Reinforcement Learning with Jigsaw Puzzles. CoRR Zifu Wang, Junyi Zhu, Bo Tang, Zhiyu Li, Feiyu Xiong, Jiaqian Yu, Matthew B. Blaschko
2025	J	`jnl`	Jigsaw-R1: A Study of Rule-based Visual Reinforcement Learning with Jigsaw Puzzles. Trans. Mach. Learn. Res. Zifu Wang, Junyi Zhu, Bo Tang, Zhiyu Li, Feiyu Xiong, Jiaqian Yu, Matthew B. Blaschko
2025	J	`jnl`	Large Language Models Reasoning Abilities Under Non-Ideal Conditions After RL-Fine-Tuning. CoRR Chang Tian, Matthew B. Blaschko, Mingzhe Xing, Xiuxing Li, Yinliang Yue, Marie-Francine Moens
2025	A*	`conf`	Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better. ICLR Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
2025	J	`jnl`	Revisiting Reweighted Risk for Calibration: AURC, Focal Loss, and Inverse Focal Loss. CoRR Han Zhou, Sebastian G. Gruber, Teodora Popordanoska, Matthew B. Blaschko
2025	J	`jnl`	SoftCFG: Uncertainty-guided Stable Guidance for Visual Autoregressive Model. CoRR Dongli Xu, Aleksei Tiulpin, Matthew B. Blaschko
2025	J	`jnl`	Surgeons versus computer vision: a comparative analysis on surgical phase recognition capabilities. Int. J. Comput. Assist. Radiol. Surg. Marco Mezzina, Pieter De Backer, Tom Vercauteren, Matthew B. Blaschko, Alexandre Mottrie, Tinne Tuytelaars
2025	J	`jnl`	Surgeons vs. Computer Vision: A comparative analysis on surgical phase recognition capabilities. CoRR Marco Mezzina, Pieter De Backer, Tom Vercauteren, Matthew B. Blaschko, Alexandre Mottrie, Tinne Tuytelaars
2025	J	`jnl`	Unlocking the Value of Decentralized Data: A Federated Dual Learning Approach for Model Aggregation. CoRR Junyi Zhu, Ruicong Yao, Taha Ceritli, Savas Özkan, Matthew B. Blaschko, Eunchung Noh, Jeongwon Min, Cho Jung Min, Mete Ozay
2025	J	`jnl`	Using Causality for Enhanced Prediction of Web Traffic Time Series. CoRR Chang Tian, Mingzhe Xing, Zenglin Shi, Matthew B. Blaschko, Yinliang Yue, Marie-Francine Moens
2025	J	`jnl`	When normalization hallucinates: unseen risks in AI-powered whole slide image processing. CoRR Karel G. M. Moons, Matthew B. Blaschko, Tinne Tuytelaars, Bart Diricx, Jonas De Vylder, Mustafa Yousif
2024	A*	`conf`	A Generic Method for Fine-grained Category Discovery in Natural Language Texts. EMNLP Chang Tian, Matthew B. Blaschko, Wenpeng Yin, Mingzhe Xing, Yinliang Yue, Marie-Francine Moens
2024	J	`jnl`	A Generic Method for Fine-grained Category Discovery in Natural Language Texts. CoRR Chang Tian, Matthew B. Blaschko, Wenpeng Yin, Mingzhe Xing, Yinliang Yue, Marie-Francine Moens
2024	J	`jnl`	A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators. CoRR Han Zhou, Jordy Van Landeghem, Teodora Popordanoska, Matthew B. Blaschko
2024	J	`jnl`	AC-IND: Sparse CT reconstruction based on attenuation coefficient estimation and implicit neural distribution. CoRR Wangduo Xie, Richard Schoonhoven, Tristan van Leeuwen, Matthew B. Blaschko
2024	A	`conf`	Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection. WACV Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
2024	A	`conf`	Beyond Document Page Classification: Design, Datasets, and Challenges. WACV Jordy Van Landeghem, Sanket Biswas, Matthew B. Blaschko, Marie-Francine Moens
2024	C	`conf`	Biological Valuation Map of Flanders: A Sentinel-2 Imagery Analysis. IGARSS Mingshi Li, Dusan Grujicic, Steven De Saeger, Stien Heremans, Ben Somers, Matthew B. Blaschko
2024	J	`jnl`	Biological Valuation Map of Flanders: A Sentinel-2 Imagery Analysis. CoRR Mingshi Li, Dusan Grujicic, Steven De Saeger, Stien Heremans, Ben Somers, Matthew B. Blaschko
2024	A*	`conf`	Can LLMs Learn by Teaching for Better Reasoning? A Preliminary Study. NeurIPS Xuefei Ning, Zifu Wang, Shiyao Li, Zinan Lin, Peiran Yao, Tianyu Fu, Matthew B. Blaschko, Guohao Dai, Huazhong Yang, Yu Wang
2024	J	`jnl`	Can LLMs Learn by Teaching? A Preliminary Study. CoRR Xuefei Ning, Zifu Wang, Shiyao Li, Zinan Lin, Peiran Yao, Tianyu Fu, Matthew B. Blaschko, Guohao Dai, Huazhong Yang, Yu Wang
2024	J	`jnl`	Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting From Multimodal Data. IEEE Trans. Medical Imaging Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin
2024	A	`conf`	Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. AISTATS Teodora Popordanoska, Sebastian Gregor Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko
2024	—	`conf`	DistilDoc: Knowledge Distillation for Visually-Rich Document Applications. ICDAR (4) Jordy Van Landeghem, Subhajit Maity, Ayan Banerjee, Matthew B. Blaschko, Marie-Francine Moens, Josep Lladós, Sanket Biswas
2024	J	`jnl`	DistilDoc: Knowledge Distillation for Visually-Rich Document Applications. CoRR Jordy Van Landeghem, Subhajit Maity, Ayan Banerjee, Matthew B. Blaschko, Marie-Francine Moens, Josep Lladós, Sanket Biswas
2024	J	`jnl`	Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs. CoRR Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
2024	—	`conf`	FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models. EMNLP (Findings) Junyi Zhu, Shuochen Liu, Yu Yu, Bo Tang, Yibo Yan, Zhiyu Li, Feiyu Xiong, Tong Xu, Matthew B. Blaschko
2024	J	`jnl`	FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models. CoRR Junyi Zhu, Shuochen Liu, Yu Yu, Bo Tang, Yibo Yan, Zhiyu Li, Feiyu Xiong, Tong Xu, Matthew B. Blaschko
2024	J	`jnl`	Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction. CoRR Jiayang Shi, Junyi Zhu, Daniël Maria Pelt, Kees Joost Batenburg, Matthew B. Blaschko
2024	J	`jnl`	Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction. Trans. Mach. Learn. Res. Jiayang Shi, Junyi Zhu, Daniël Maria Pelt, Kees Joost Batenburg, Matthew B. Blaschko
2024	A	`conf`	Improving Multimodal Learning with Multi-Loss Gradient Modulation. BMVC Konstantinos Kontras, Christos Chatzichristos, Matthew B. Blaschko, Maarten De Vos
2024	J	`jnl`	Improving Multimodal Learning with Multi-Loss Gradient Modulation. CoRR Konstantinos Kontras, Christos Chatzichristos, Matthew B. Blaschko, Maarten De Vos
2024	A*	`conf`	LaSCal: Label-Shift Calibration without target labels. NeurIPS Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko
2024	—	`conf`	Laparoflow-SSL: Image Analysis From a Tiny Dataset Through Self-Supervised Transformers Leveraging Unlabeled Surgical Video. MIDL Karel G. M. Moons, Jonas De Vylder, Matthew B. Blaschko, Tinne Tuytelaars
2024	J	`jnl`	Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better. CoRR Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
2024	J	`jnl`	Mitigating Bias in Bayesian Optimized Data While Designing MacPherson Suspension Architecture. IEEE Trans. Artif. Intell. Sinnu Susan Thomas, Guillaume Lamine, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
2024	—	`conf`	Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting. ICDAR (4) Omar Hamed, Souhail Bakkali, Matthew B. Blaschko, Sien Moens, Jordy Van Landeghem
2024	J	`jnl`	Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting. CoRR Omar Hamed, Souhail Bakkali, Marie-Francine Moens, Matthew B. Blaschko, Jordy Van Landeghem
2024	J	`jnl`	Multimodal Fusion Balancing Through Game-Theoretic Regularization. CoRR Konstantinos Kontras, Thomas Strypsteen, Christos Chatzichristos, Paul P. Liang, Matthew B. Blaschko, Maarten De Vos
2024	J	`jnl`	Redundancy-Aware Camera Selection for Indoor Scene Neural Rendering. CoRR Zehao Wang, Han Zhou, Matthew B. Blaschko, Tinne Tuytelaars, Minye Wu
2024	—	`conf`	Rescaling Intermediate Features Makes Trained Consistency Models Perform Better. Tiny Papers @ ICLR Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko
2024	J	`jnl`	Temporal Transferability of Tree Species Classification in Temperate Forests with Sentinel-2 Time Series. Remote. Sens. Margot Verhulst, Stien Heremans, Matthew B. Blaschko, Ben Somers
2024	J	`jnl`	The Common Stability Mechanism behind most Self-Supervised Learning Approaches. CoRR Abhishek Jha, Matthew B. Blaschko, Yuki M. Asano, Tinne Tuytelaars
2024	A*	`conf`	Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation? NeurIPS Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus H. Maier-Hein, Paul F. 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, Jia-Xin Zhuang, Hao Chen, Holger Roth, Daguang Xu, Matthew B. Blaschko, Sergio Decherchi, Andrea Cavalli, Alan L. Yuille, Zongwei Zhou
2024	J	`jnl`	Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation? CoRR Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus H. Maier-Hein, Paul F. 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
2023	C	`conf`	A Corrected Expected Improvement Acquisition Function Under Noisy Observations. ACML Han Zhou, Xingchen Ma, Matthew B. Blaschko
2023	J	`jnl`	A Corrected Expected Improvement Acquisition Function Under Noisy Observations. CoRR Han Zhou, Xingchen Ma, Matthew B. Blaschko
2023	J	`jnl`	A generalizable deep learning regression model for automated glaucoma screening from fundus images. npj Digit. Medicine Ruben Hemelings, Bart Elen, Alexander K. Schuster, Matthew B. Blaschko, João Barbosa Breda, Pekko Hujanen, Annika Junglas, Stefan Nickels, Andrew White, Norbert Pfeiffer, Paul Mitchell, Patrick De Boever, Anja Tuulonen, Ingeborg Stalmans
2023	J	`jnl`	Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection. CoRR Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
2023	J	`jnl`	Beyond Document Page Classification: Design, Datasets, and Challenges. CoRR Jordy Van Landeghem, Sanket Biswas, Matthew B. Blaschko, Marie-Francine Moens
2023	A*	`conf`	Confidence-Aware Personalized Federated Learning via Variational Expectation Maximization. CVPR Junyi Zhu, Xingchen Ma, Matthew B. Blaschko
2023	J	`jnl`	Confidence-aware Personalized Federated Learning via Variational Expectation Maximization. CoRR Junyi Zhu, Xingchen Ma, Matthew B. Blaschko
2023	J	`jnl`	Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors. CoRR Teodora Popordanoska, Sebastian G. Gruber, Aleksei Tiulpin, Florian Büttner, Matthew B. Blaschko
2023	—	`conf`	Dense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction. MICCAI (1) Wangduo Xie, Matthew B. Blaschko
2023	J	`jnl`	Dense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction. CoRR Wangduo Xie, Matthew B. Blaschko
2023	—	`conf`	Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels. MICCAI (3) Zifu Wang, Teodora Popordanoska, Jeroen Bertels, Robin Lemmens, Matthew B. Blaschko
2023	J	`jnl`	Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels. CoRR Zifu Wang, Teodora Popordanoska, Jeroen Bertels, Robin Lemmens, Matthew B. Blaschko
2023	A*	`conf`	Document Understanding Dataset and Evaluation (DUDE). ICCV Jordy Van Landeghem, Rafal Powalski, Rubèn Tito, Dawid Jurkiewicz, Matthew B. Blaschko, Lukasz Borchmann, Mickaël Coustaty, Sien Moens, Michal Pietruszka, Bertrand Anckaert, Tomasz Stanislawek, Pawel Józiak, Ernest Valveny
2023	J	`jnl`	Document Understanding Dataset and Evaluation (DUDE). CoRR Jordy Van Landeghem, Rubèn Tito, Lukasz Borchmann, Michal Pietruszka, Pawel Józiak, Rafal Powalski, Dawid Jurkiewicz, Mickaël Coustaty, Bertrand Anckaert, Ernest Valveny, Matthew B. Blaschko, Sien Moens, Tomasz Stanislawek
2023	J	`jnl`	Estimating calibration error under label shift without labels. CoRR Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko
2023	—	`conf`	Improved Imagery Throughput via Cascaded Uncertainty Pruning on U-Net++. NLDL Mingshi Li, Zifu Wang, Matthew B. Blaschko
2023	J	`jnl`	Improving Differentially Private SGD via Randomly Sparsified Gradients. Trans. Mach. Learn. Res. Junyi Zhu, Matthew B. Blaschko
2023	A*	`conf`	Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels. NeurIPS Zifu Wang, Xuefei Ning, Matthew B. Blaschko
2023	J	`jnl`	Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels. CoRR Zifu Wang, Matthew B. Blaschko
2023	J	`jnl`	Kinematics Design of a MacPherson Suspension Architecture Based on Bayesian Optimization. IEEE Trans. Cybern. Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
2023	A*	`conf`	Multimodal Distillation for Egocentric Action Recognition. ICCV Gorjan Radevski, Dusan Grujicic, Matthew B. Blaschko, Marie-Francine Moens, Tinne Tuytelaars
2023	J	`jnl`	Multimodal Distillation for Egocentric Action Recognition. CoRR Gorjan Radevski, Dusan Grujicic, Marie-Francine Moens, Matthew B. Blaschko, Tinne Tuytelaars
2023	A*	`conf`	Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union. NeurIPS Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko
2023	J	`jnl`	Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union. CoRR Zifu Wang, Maxim Berman, Amal Rannen Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko
2023	A*	`conf`	Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning. ICML Junyi Zhu, Ruicong Yao, Matthew B. Blaschko
2023	J	`jnl`	Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning. CoRR Junyi Zhu, Ruicong Yao, Matthew B. Blaschko
2023	J	`jnl`	Understanding metric-related pitfalls in image analysis validation. CoRR Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein
2022	B	`conf`	2-D latent space models: Layer-wise perceptual training and spatial grounding. ICPR Dusan Grujicic, Matthew B. Blaschko
2022	A*	`conf`	A Consistent and Differentiable Lp Canonical Calibration Error Estimator. NeurIPS Teodora Popordanoska, Raphael Sayer, Matthew B. Blaschko
2022	J	`jnl`	A Consistent and Differentiable Lp Canonical Calibration Error Estimator. CoRR Teodora Popordanoska, Raphael Sayer, Matthew B. Blaschko
2022	J	`jnl`	Benchmarking Scalable Predictive Uncertainty in Text Classification. IEEE Access Jordy Van Landeghem, Matthew B. Blaschko, Bertrand Anckaert, Marie-Francine Moens
2022	—	`conf`	CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting. ISBI Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
2022	J	`jnl`	Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting from Multimodal Data. CoRR Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin
2022	B	`conf`	Combinatorial optimization for low bit-width neural networks. ICPR Han Zhou, Aida Ashrafi, Matthew B. Blaschko
2022	J	`jnl`	Combinatorial optimization for low bit-width neural networks. CoRR Han Zhou, Aida Ashrafi, Matthew B. Blaschko
2022	J	`jnl`	Designing MacPherson Suspension Architectures using Bayesian Optimization. CoRR Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
2022	J	`jnl`	Greedy Bayesian Posterior Approximation with Deep Ensembles. Trans. Mach. Learn. Res. Aleksei Tiulpin, Matthew B. Blaschko
2022	—	`conf`	KULeuven at LeQua 2022: Model Calibration in Quantification Learning. CLEF (Working Notes) Teodora Popordanoska, Matthew B. Blaschko
2022	—	`conf`	MRF-UNets: Searching UNet with Markov Random Fields. ECML/PKDD (3) Zifu Wang, Matthew B. Blaschko
2022	J	`jnl`	MRF-UNets: Searching UNet with Markov Random Fields. CoRR Zifu Wang, Matthew B. Blaschko
2022	J	`jnl`	On confidence intervals for precision matrices and the eigendecomposition of covariance matrices. CoRR Teodora Popordanoska, Aleksei Tiulpin, Wacha Bounliphone, Matthew B. Blaschko
2022	—	`conf`	Optimizing Slimmable Networks for Multiple Target Platforms. NLDL Zifu Wang, Matthew B. Blaschko
2022	A*	`conf`	Predicting Physical World Destinations for Commands Given to Self-Driving Cars. AAAI Dusan Grujicic, Thierry Deruyttere, Marie-Francine Moens, Matthew B. Blaschko
2022	J	`jnl`	Students taught by multimodal teachers are superior action recognizers. CoRR Gorjan Radevski, Dusan Grujicic, Matthew B. Blaschko, Marie-Francine Moens, Tinne Tuytelaars
2022	J	`jnl`	Talk2Car: Predicting Physical Trajectories for Natural Language Commands. IEEE Access Thierry Deruyttere, Dusan Grujicic, Matthew B. Blaschko, Marie-Francine Moens
2021	J	`jnl`	Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation. IEEE Trans. Pattern Anal. Mach. Intell. Xingchen Ma, Matthew B. Blaschko
2021	J	`jnl`	DeepProg: A Transformer-based Framework for Predicting Disease Prognosis. CoRR Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
2021	J	`jnl`	Differentially Private SGD with Sparse Gradients. CoRR Junyi Zhu, Matthew B. Blaschko
2021	J	`jnl`	Glaucoma detection beyond the optic disc: The importance of the peripapillary region using explainable deep learning. CoRR Ruben Hemelings, Bart Elen, João Barbosa Breda, Matthew B. Blaschko, Patrick De Boever, Ingeborg Stalmans
2021	J	`jnl`	Greedy Bayesian Posterior Approximation with Deep Ensembles. CoRR Aleksei Tiulpin, Matthew B. Blaschko
2021	A*	`conf`	Meta-Cal: Well-controlled Post-hoc Calibration by Ranking. ICML Xingchen Ma, Matthew B. Blaschko
2021	J	`jnl`	Meta-Cal: Well-controlled Post-hoc Calibration by Ranking. CoRR Xingchen Ma, Matthew B. Blaschko
2021	—	`conf`	On the Relationship Between Calibrated Predictors and Unbiased Volume Estimation. MICCAI (1) Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko
2021	J	`jnl`	On the relationship between calibrated predictors and unbiased volume estimation. CoRR Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko
2021	J	`jnl`	Pathological myopia classification with simultaneous lesion segmentation using deep learning. Comput. Methods Programs Biomed. Ruben Hemelings, Bart Elen, Matthew B. Blaschko, Julie Jacob, Ingeborg Stalmans, Patrick De Boever
2021	J	`jnl`	Pointwise visual field estimation from optical coherence tomography in glaucoma: a structure-function analysis using deep learning. CoRR Ruben Hemelings, Bart Elen, João Barbosa Breda, Erwin Bellon, Matthew B. Blaschko, Patrick De Boever, Ingeborg Stalmans
2021	—	`conf`	Post Training Uncertainty Calibration Of Deep Networks For Medical Image Segmentation. ISBI Axel-Jan Rousseau, Thijs Becker, Jeroen Bertels, Matthew B. Blaschko, Dirk Valkenborg
2021	J	`jnl`	Predicting Physical World Destinations for Commands Given to Self-Driving Cars. CoRR Dusan Grujicic, Thierry Deruyttere, Marie-Francine Moens, Matthew B. Blaschko
2021	A*	`conf`	R-GAP: Recursive Gradient Attack on Privacy. ICLR Junyi Zhu, Matthew B. Blaschko
2021	C	`conf`	Remote Sensing and Deep Learning for Environmental Policy Support: From Theory to Practice. IGARSS Stien Heremans, Francis Turkelboom, Margot Verhulst, Matthew B. Blaschko, Ben Somers
2020	A*	`conf`	AOWS: Adaptive and Optimal Network Width Search With Latency Constraints. CVPR Maxim Berman, Leonid Pishchulin, Ning Xu, Matthew B. Blaschko, Gérard G. Medioni
2020	J	`jnl`	AOWS: Adaptive and optimal network width search with latency constraints. CoRR Maxim Berman, Leonid Pishchulin, Ning Xu, Matthew B. Blaschko, Gérard G. Medioni
2020	J	`jnl`	Additive Tree-Structured Conditional Parameter Spaces in Bayesian Optimization: A Novel Covariance Function and a Fast Implementation. CoRR Xingchen Ma, Matthew B. Blaschko
2020	A	`conf`	Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization. AISTATS Xingchen Ma, Matthew B. Blaschko
2020	J	`jnl`	Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization. CoRR Xingchen Ma, Matthew B. Blaschko
2020	—	`conf`	Commands 4 Autonomous Vehicles (C4AV) Workshop Summary. ECCV Workshops (2) Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew B. Blaschko, Tinne Tuytelaars, Marie-Francine Moens
2020	J	`jnl`	Commands 4 Autonomous Vehicles (C4AV) Workshop Summary. CoRR Thierry Deruyttere, Simon Vandenhende, Dusan Grujicic, Yu Liu, Luc Van Gool, Matthew B. Blaschko, Tinne Tuytelaars, Marie-Francine Moens
2020	J	`jnl`	Discriminative Training of Conditional Random Fields with Probably Submodular Constraints. Int. J. Comput. Vis. Maxim Berman, Matthew B. Blaschko
2020	B	`conf`	Learning to ground medical text in a 3D human atlas. CoNLL Dusan Grujicic, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko
2020	J	`jnl`	Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index. IEEE Trans. Medical Imaging Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
2020	J	`jnl`	Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index. CoRR Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
2020	J	`jnl`	Pathological myopia classification with simultaneous lesion segmentation using deep learning. CoRR Ruben Hemelings, Bart Elen, Matthew B. Blaschko, Julie Jacob, Ingeborg Stalmans, Patrick De Boever
2020	J	`jnl`	R-GAP: Recursive Gradient Attack on Privacy. CoRR Junyi Zhu, Matthew B. Blaschko
2020	J	`jnl`	Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading From Plain Radiographs. IEEE Trans. Medical Imaging Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
2020	J	`jnl`	Semixup: In- and Out-of-Manifold Regularization for Deep Semi-Supervised Knee Osteoarthritis Severity Grading from Plain Radiographs. CoRR Huy Hoang Nguyen, Simo Saarakkala, Matthew B. Blaschko, Aleksei Tiulpin
2020	J	`jnl`	The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses. IEEE Trans. Pattern Anal. Mach. Intell. Jiaqian Yu, Matthew B. Blaschko
2019	A*	`conf`	A Bayesian Optimization Framework for Neural Network Compression. ICCV Xingchen Ma, Amal Rannen Triki, Maxim Berman, Christos Sagonas, Jacques Calì, Matthew B. Blaschko
2019	A	`conf`	Adaptive Compression-based Lifelong Learning. BMVC Shivangi Srivastava, Maxim Berman, Matthew B. Blaschko, Devis Tuia
2019	J	`jnl`	Adaptive Compression-based Lifelong Learning. CoRR Shivangi Srivastava, Maxim Berman, Matthew B. Blaschko, Devis Tuia
2019	J	`jnl`	Artery-vein segmentation in fundus images using a fully convolutional network. Comput. Medical Imaging Graph. Ruben Hemelings, Bart Elen, Ingeborg Stalmans, Karel van Keer, Patrick De Boever, Matthew B. Blaschko
2019	—	`conf`	Designing MacPherson Suspension Architectures Using Bayesian Optimization. BNAIC/BENELEARN Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-Ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
2019	J	`jnl`	Discriminative training of conditional random fields with probably submodular constraints. CoRR Maxim Berman, Matthew B. Blaschko
2019	—	`conf`	Function Norms for Neural Networks. ICCV Workshops Amal Rannen-Triki, Maxim Berman, Vladimir Kolmogorov, Matthew B. Blaschko
2019	J	`jnl`	Generating superpixels using deep image representations. CoRR Thomas Verelst, Matthew B. Blaschko, Maxim Berman
2019	J	`jnl`	Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice. CoRR Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
2019	—	`conf`	Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice. MICCAI (2) Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko
2019	J	`jnl`	Scattering Networks for Hybrid Representation Learning. IEEE Trans. Pattern Anal. Mach. Intell. Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
2018	J	`jnl`	An ensemble deep learning based approach for red lesion detection in fundus images. Comput. Methods Programs Biomed. José Ignacio Orlando, Elena Prokofyeva, Mariana del Fresno, Matthew B. Blaschko
2018	J	`jnl`	Efficient semantic image segmentation with superpixel pooling. CoRR Mathijs Schuurmans, Maxim Berman, Matthew B. Blaschko
2018	J	`jnl`	Intraoperative margin assessment of human breast tissue in optical coherence tomography images using deep neural networks. Comput. Medical Imaging Graph. Amal Rannen Triki, Matthew B. Blaschko, Yoon Mo Jung, Seungri Song, Hyun Ju Han, Seung Il Kim, Chulmin Joo
2018	J	`jnl`	Scattering Networks for Hybrid Representation Learning. CoRR Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky
2018	B	`conf`	Shallow and Deep Models for Domain Adaptation problems. ESANN Siamak Mehrkanoon, Matthew B. Blaschko, Johan A. K. Suykens
2018	J	`jnl`	Supermodular Locality Sensitive Hashes. CoRR Maxim Berman, Matthew B. Blaschko
2018	A*	`conf`	The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks. CVPR Maxim Berman, Amal Rannen Triki, Matthew B. Blaschko
2018	—	`conf`	Towards a Glaucoma Risk Index Based on Simulated Hemodynamics from Fundus Images. MICCAI (2) José Ignacio Orlando, João Barbosa Breda, Karel van Keer, Matthew B. Blaschko, Pablo J. Blanco, Carlos A. Bulant
2018	J	`jnl`	Towards a glaucoma risk index based on simulated hemodynamics from fundus images. CoRR José Ignacio Orlando, João Barbosa Breda, Karel van Keer, Matthew B. Blaschko, Pablo J. Blanco, Carlos A. Bulant
2018	J	`jnl`	Yes, IoU loss is submodular - as a function of the mispredictions. CoRR Maxim Berman, Matthew B. Blaschko, Amal Rannen Triki, Jiaqian Yu
2017	J	`jnl`	A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images. IEEE Trans. Biomed. Eng. José Ignacio Orlando, Elena Prokofyeva, Matthew B. Blaschko
2017	J	`jnl`	An Efficient Decomposition Framework for Discriminative Segmentation with Supermodular Losses. CoRR Jiaqian Yu, Matthew B. Blaschko
2017	A*	`conf`	Encoder Based Lifelong Learning. ICCV Amal Rannen Triki, Rahaf Aljundi, Matthew B. Blaschko, Tinne Tuytelaars
2017	J	`jnl`	Encoder Based Lifelong Learning. CoRR Amal Rannen Triki, Rahaf Aljundi, Matthew B. Blaschko, Tinne Tuytelaars
2017	—	`conf`	Joint Embeddings of Scene Graphs and Images. ICLR (Workshop) Eugene Belilovsky, Matthew B. Blaschko, Jamie Ryan Kiros, Raquel Urtasun, Richard S. Zemel
2017	J	`jnl`	Learning to Detect Red Lesions in Fundus Photographs: An Ensemble Approach based on Deep Learning. CoRR José Ignacio Orlando, Elena Prokofyeva, Mariana del Fresno, Matthew B. Blaschko
2017	—	`conf`	Learning to Discover Sparse Graphical Models. ICLR (Workshop) Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko
2017	A*	`conf`	Learning to Discover Sparse Graphical Models. ICML Eugene Belilovsky, Kyle Kastner, Gaël Varoquaux, Matthew B. Blaschko
2017	J	`jnl`	Optimization of the Jaccard index for image segmentation with the Lovász hinge. CoRR Maxim Berman, Matthew B. Blaschko
2017	—	`conf`	Slack and Margin Rescaling as Convex Extensions of Supermodular Functions. EMMCVPR Matthew B. Blaschko
2017	J	`jnl`	Stochastic Weighted Function Norm Regularization. CoRR Amal Rannen Triki, Maxim Berman, Matthew B. Blaschko
2016	A	`conf`	A Convex Surrogate Operator for General Non-Modular Loss Functions. AISTATS Jiaqian Yu, Matthew B. Blaschko
2016	J	`jnl`	A Convex Surrogate Operator for General Non-Modular Loss Functions. CoRR Jiaqian Yu, Matthew B. Blaschko
2016	A*	`conf`	A Test of Relative Similarity For Model Selection in Generative Models. ICLR (Poster) Wacha Bounliphone, Eugene Belilovsky, Matthew B. Blaschko, Ioannis Antonoglou, Arthur Gretton
2016	J	`jnl`	Discovering predictors of mental health service utilization with k-support regularized logistic regression. Inf. Sci. Hakim Sidahmed, Elena Prokofyeva, Matthew B. Blaschko
2016	A	`conf`	Discriminative training of CRF models with probably submodular constraints. WACV Wojciech Zaremba, Matthew B. Blaschko
2016	A	`conf`	Efficient Learning for Discriminative Segmentation with Supermodular Losses. BMVC Jiaqian Yu, Matthew B. Blaschko
2016	A*	`conf`	Efficient, dense, object-based segmentation from RGBD video. ICRA Mahsa Ghafarianzadeh, Matthew B. Blaschko, Gabe Sibley
2016	J	`jnl`	Fast Non-Parametric Tests of Relative Dependency and Similarity. CoRR Wacha Bounliphone, Eugene Belilovsky, Arthur Tenenhaus, Ioannis Antonoglou, Arthur Gretton, Matthew B. Blaschko
2016	J	`jnl`	Slack and Margin Rescaling as Convex Extensions of Supermodular Functions. CoRR Matthew B. Blaschko
2016	J	`jnl`	Stochastic Function Norm Regularization of Deep Networks. CoRR Amal Rannen Triki, Matthew B. Blaschko
2016	—	`conf`	Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity. NIPS Eugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko
2016	J	`jnl`	The pyramid quantized Weisfeiler-Lehman graph representation. Neurocomputing Katerina Gkirtzou, Matthew B. Blaschko
2015	A*	`conf`	A low variance consistent test of relative dependency. ICML Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus, Matthew B. Blaschko
2015	J	`jnl`	Convex relaxations of penalties for sparse correlated variables with bounded total variation. Mach. Learn. Eugene Belilovsky, Andreas Argyriou, Gaël Varoquaux, Matthew B. Blaschko
2015	A*	`conf`	Learning Submodular Losses with the Lovasz Hinge. ICML Jiaqian Yu, Matthew B. Blaschko
2015	J	`jnl`	Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm. Comput. Medical Imaging Graph. Eugene Belilovsky, Katerina Gkirtzou, Michail Misyrlis, Anna B. Konova, Jean Honorio, Nelly Alia-Klein, Rita Z. Goldstein, Dimitris Samaras, Matthew B. Blaschko
2015	J	`jnl`	The Lovász Hinge: A Convex Surrogate for Submodular Losses. CoRR Jiaqian Yu, Matthew B. Blaschko
2014	J	`jnl`	A low variance consistent test of relative dependency. CoRR Wacha Bounliphone, Arthur Gretton, Matthew B. Blaschko
2014	—	`conf`	An GCPR Matthew B. Blaschko, Arpit Mittal, Esa Rahtu
2014	—	`conf`	Learning Fully-Connected CRFs for Blood Vessel Segmentation in Retinal Images. MICCAI (1) José Ignacio Orlando, Matthew B. Blaschko
2014	A*	`conf`	Understanding Objects in Detail with Fine-Grained Attributes. CVPR Andrea Vedaldi, Siddharth Mahendran, Stavros Tsogkas, Subhransu Maji, Ross B. Girshick, Juho Kannala, Esa Rahtu, Iasonas Kokkinos, Matthew B. Blaschko, David J. Weiss, Ben Taskar, Karen Simonyan, Naomi Saphra, Sammy Mohamed
2014	A	`conf`	Unsupervised Spatio-Temporal Segmentation with Sparse Spectral-Clustering. BMVC Mahsa Ghafarianzadeh, Matthew B. Blaschko, Gabe Sibley
2013	J	`jnl`	A Note on k-support Norm Regularized Risk Minimization CoRR Matthew B. Blaschko
2013	—	`conf`	B-test: A Non-parametric, Low Variance Kernel Two-sample Test. NIPS Wojciech Zaremba, Arthur Gretton, Matthew B. Blaschko
2013	J	`jnl`	B-test: A Non-parametric, Low Variance Kernel Two-sample Test. CoRR Wojciech Zaremba, Arthur Gretton, Matthew B. Blaschko
2013	—	`conf`	FMRI analysis of cocaine addiction using k-support sparsity. ISBI Katerina Gkirtzou, Jean Honorio, Dimitris Samaras, Rita Z. Goldstein, Matthew B. Blaschko
2013	J	`jnl`	Fine-Grained Visual Classification of Aircraft. CoRR Subhransu Maji, Esa Rahtu, Juho Kannala, Matthew B. Blaschko, Andrea Vedaldi
2013	—	`conf`	Learning from M/EEG Data with Variable Brain Activation Delays. IPMI Wojciech Zaremba, M. Pawan Kumar, Alexandre Gramfort, Matthew B. Blaschko
2013	—	`conf`	Non Maximal Suppression in Cascaded Ranking Models. SCIA Matthew B. Blaschko, Juho Kannala, Esa Rahtu
2013	—	`conf`	Sparse Classification with MRI Based Markers for Neuromuscular Disease Categorization. MLMI Katerina Gkirtzou, Jean-François Deux, Guillaume Bassez, Aristeidis Sotiras, Alain Rahmouni, Thibault Varacca, Nikos Paragios, Matthew B. Blaschko
2013	—	`conf`	Taxonomic Prediction with Tree-Structured Covariances. ECML/PKDD (2) Matthew B. Blaschko, Wojciech Zaremba, Arthur Gretton
2013	—	`conf`	fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics. MLMI Katerina Gkirtzou, Jean Honorio, Dimitris Samaras, Rita Z. Goldstein, Matthew B. Blaschko
2012	J	`jnl`	Guest Editorial: Special Issue on Structured Prediction and Inference. Int. J. Comput. Vis. Matthew B. Blaschko, Christoph H. Lampert
2012	—	`conf`	Perceptron Learning of SAT. NIPS Alex Flint, Matthew B. Blaschko
2012	—	`conf`	Taxonomic Multi-class Prediction and Person Layout Using Efficient Structured Ranking. ECCV (2) Arpit Mittal, Matthew B. Blaschko, Andrew Zisserman, Philip H. S. Torr
2011	—	`conf`	Branch and Bound Strategies for Non-maximal Suppression in Object Detection. EMMCVPR Matthew B. Blaschko
2011	A*	`conf`	Learning a category independent object detection cascade. ICCV Esa Rahtu, Juho Kannala, Matthew B. Blaschko
2011	A*	`conf`	Learning equivariant structured output SVM regressors. ICCV Andrea Vedaldi, Matthew B. Blaschko, Andrew Zisserman
2011	J	`jnl`	Semi-supervised kernel canonical correlation analysis with application to human fMRI. Pattern Recognit. Lett. Matthew B. Blaschko, Jacquelyn A. Shelton, Andreas M. Bartels, Christoph H. Lampert, Arthur Gretton
2010	—	`conf`	Simultaneous Object Detection and Ranking with Weak Supervision. NIPS Matthew B. Blaschko, Andrea Vedaldi, Andrew Zisserman
2010	J	`jnl`	Unsupervised Object Discovery: A Comparison. Int. J. Comput. Vis. Tinne Tuytelaars, Christoph H. Lampert, Matthew B. Blaschko, Wray L. Buntine
2009	—	`conf`	Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity. NIPS Matthew B. Blaschko, Jacquelyn A. Shelton, Andreas M. Bartels
2009	J	`jnl`	Efficient Subwindow Search: A Branch and Bound Framework for Object Localization. IEEE Trans. Pattern Anal. Mach. Intell. Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann
2009	A	`conf`	Object Localization with Global and Local Context Kernels. BMVC Matthew B. Blaschko, Christoph H. Lampert
2009	J	`jnl`	Structured prediction by joint kernel support estimation. Mach. Learn. Christoph H. Lampert, Matthew B. Blaschko
2008	—	`conf`	A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery. MLG@ICML Matthew B. Blaschko, Arthur Gretton
2008	—	`conf`	A Multiple Kernel Learning Approach to Joint Multi-class Object Detection. DAGM-Symposium Christoph H. Lampert, Matthew B. Blaschko
2008	A*	`conf`	Beyond sliding windows: Object localization by efficient subwindow search. CVPR Christoph H. Lampert, Matthew B. Blaschko, Thomas Hofmann
2008	A*	`conf`	Correlational spectral clustering. CVPR Matthew B. Blaschko, Christoph H. Lampert
2008	—	`conf`	Learning Taxonomies by Dependence Maximization. NIPS Matthew B. Blaschko, Arthur Gretton
2008	—	`conf`	Learning to Localize Objects with Structured Output Regression. ECCV (1) Matthew B. Blaschko, Christoph H. Lampert
2008	—	`conf`	Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis. ECML/PKDD (1) Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton
2005	—	`conf`	Automatic In Situ Identification of Plankton. WACV/MOTION Matthew B. Blaschko, Gary Holness, Marwan A. Mattar, Dimitri A. Lisin, Paul E. Utgoff, Allen R. Hanson, Howard J. Schultz, Edward M. Riseman, Michael E. Sieracki, William M. Balch, Ben Tupper
2005	—	`conf`	Combining Local and Global Image Features for Object Class Recognition. CVPR Workshops Dimitri A. Lisin, Marwan A. Mattar, Matthew B. Blaschko, Erik G. Learned-Miller, Mark C. Benfield