Efficient Classification of Images with Taxonomies. - Alexander Binder; Motoaki Kawanabe; Ulf Brefeld (ACCV (3), 2009)

A procedure of adaptive kernel combination with kernel-target alignment for object classification. - Motoaki Kawanabe; Shinichi Nakajima; Alexander Binder (CIVR, 2009)

Enhancing Recognition of Visual Concepts with Primitive Color Histograms via Non-sparse Multiple Kernel Learning. - Alexander Binder; Motoaki Kawanabe (CLEF (2), 2009)

Fraunhofer FIRST's Submission to ImageCLEF2009 Photo Annotation Task: Non-sparse Multiple Kernel Learning. - Alexander Binder; Motoaki Kawanabe (CLEF (Working Notes), 2009)

A Hybrid Supervised-Unsupervised Vocabulary Generation Algorithm for Visual Concept Recognition. - Alexander Binder; Wojciech Wojcikiewicz; Christina Müller; Motoaki Kawanabe (ACCV (3), 2010)

Shrinking large visual vocabularies using multi-label agglomerative information bottleneck. - Wojciech Wojcikiewicz; Alexander Binder; Motoaki Kawanabe (ICIP, 2010)

Enhancing Image Classification with Class-wise Clustered Vocabularies. - Wojciech Wojcikiewicz; Alexander Binder; Motoaki Kawanabe (ICPR, 2010)

The SHOGUN Machine Learning Toolbox. - Sören Sonnenburg; Gunnar Rätsch; Sebastian Henschel; Christian Widmer; Jonas Behr; Alexander Zien; Fabio De Bona; Alexander Binder; Christian Gehl; Vojtech Franc (J. Mach. Learn. Res., 2010)

Multi-task Learning via Non-sparse Multiple Kernel Learning. - Wojciech Samek; Alexander Binder; Motoaki Kawanabe (CAIP (1), 2011)

The Joint Submission of the TU Berlin and Fraunhofer FIRST (TUBFI) to the ImageCLEF2011 Photo Annotation Task. - Alexander Binder; Wojciech Samek; Marius Kloft; Christina Müller; Klaus-Robert Müller; Motoaki Kawanabe (CLEF (Notebook Papers/Labs/Workshop), 2011)

Multi-modal visual concept classification of images via Markov random walk over tags. - Motoaki Kawanabe; Alexander Binder; Christina Müller; Wojciech Wojcikiewicz (WACV, 2011)

Insights from Classifying Visual Concepts with Multiple Kernel Learning - Alexander Binder; Shinichi Nakajima; Marius Kloft; Christina Müller; Wojciech Samek; Ulf Brefeld; Klaus-Robert Müller; Motoaki Kawanabe (CoRR, 2011)

On Taxonomies for Multi-class Image Categorization. - Alexander Binder; Klaus-Robert Müller; Motoaki Kawanabe (Int. J. Comput. Vis., 2012)

Multiple Kernel Learning for Brain-Computer Interfacing. - Wojciech Samek; Alexander Binder; Klaus-Robert Müller (EMBC, 2013)

Identification of vehicle tracks and association to wireless endpoints by multiple sensor modalities. - Daniel Becker 004; Jens Einsiedler; Bernd Schäufele; Alexander Binder; Ilja Radusch (IPIN, 2013)

Enhanced representation and multi-task learning for image annotation. - Alexander Binder; Wojciech Samek; Klaus-Robert Müller; Motoaki Kawanabe (Comput. Vis. Image Underst., 2013)

Bag of Machine Learning Concepts for Visual Concept Recognition in Images. - Alexander Binder (2013)

Learning and Evaluation in Presence of Non-i.i.d. Label Noise. - Nico Görnitz; Anne Porbadnigk; Alexander Binder; Claudia Sannelli; Mikio L. Braun; Klaus-Robert Müller; Marius Kloft (AISTATS, 2014)

When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning. - Anne K. Porbadnigk; Nico Görnitz; Claudia Sannelli; Alexander Binder; Mikio L. Braun; Marius Kloft; Klaus-Robert Müller (BCI, 2014)

Multi-modal identification and tracking of vehicles in partially observed environments. - Daniel Becker 004; Alexander Binder; Jens Einsiedler; Ilja Radusch (IPIN, 2014)

Machine Learning for Visual Concept Recognition and Ranking for Images. - Alexander Binder; Wojciech Samek; Klaus-Robert Müller; Motoaki Kawanabe (Towards the Internet of Services, 2014)

Theory and Algorithms for the Localized Setting of Learning Kernels. - Yunwen Lei; Alexander Binder; Ürün Dogan; Marius Kloft (FE@NIPS, 2015)

Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms. - Yunwen Lei; Ürün Dogan; Alexander Binder; Marius Kloft (NIPS, 2015)

Extracting latent brain states - Towards true labels in cognitive neuroscience experiments. - Anne K. Porbadnigk; Nico Görnitz; Claudia Sannelli; Alexander Binder; Mikio L. Braun; Marius Kloft; Klaus-Robert Müller (NeuroImage, 2015)

Localized Multiple Kernel Learning - A Convex Approach. - Yunwen Lei; Alexander Binder; Ürün Dogan; Marius Kloft (ACML, 2016)

Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. - Sebastian Lapuschkin; Alexander Binder; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CVPR, 2016)

Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. - Alexander Binder; Grégoire Montavon; Sebastian Lapuschkin; Klaus-Robert Müller; Wojciech Samek (ICANN (2), 2016)

Controlling explanatory heatmap resolution and semantics via decomposition depth. - Sebastian Bach; Alexander Binder; Klaus-Robert Müller; Wojciech Samek (ICIP, 2016)

Zero Shot Learning for Semantic Boundary Detection - How Far Can We Get? - Jing Yu Koh; Wojciech Samek; Klaus-Robert Müller; Alexander Binder (CoRR, 2016)

Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation. - Wojciech Samek; Grégoire Montavon; Alexander Binder; Sebastian Lapuschkin; Klaus-Robert Müller (CoRR, 2016)

The LRP Toolbox for Artificial Neural Networks. - Sebastian Lapuschkin; Alexander Binder; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (J. Mach. Learn. Res., 2016)

ImageCLEF 2017: ImageCLEF Tuberculosis Task - the SGEast Submission. - Jiamei Sun; Penny Chong; Yi Xiang Marcus Tan; Alexander Binder (CLEF (Working Notes), 2017)

Object Boundary Detection and Classification with Image-Level Labels. - Jing Yu Koh; Wojciech Samek; Klaus-Robert Müller; Alexander Binder (GCPR, 2017)

Understanding and Comparing Deep Neural Networks for Age and Gender Classification. - Wojciech Samek; Alexander Binder; Sebastian Lapuschkin; Klaus-Robert Müller (ICCV Workshops, 2017)

Explaining nonlinear classification decisions with deep Taylor decomposition. - Grégoire Montavon; Sebastian Lapuschkin; Alexander Binder; Wojciech Samek; Klaus-Robert Müller (Pattern Recognit., 2017)

Evaluating the Visualization of What a Deep Neural Network Has Learned. - Wojciech Samek; Alexander Binder; Grégoire Montavon; Sebastian Lapuschkin; Klaus-Robert Müller (IEEE Trans. Neural Networks Learn. Syst., 2017)

Urban Zoning Using Higher-Order Markov Random Fields on Multi-View Imagery Data. - Tian Feng 001; Quang-Trung Truong; Duc Thanh Nguyen; Jing Yu Koh; Lap-Fai Yu; Alexander Binder; Sai-Kit Yeung (ECCV (8), 2018)

Corplab INLI@FIRE-2018: Identification of Indian Native Language using Pairwise Coupling. - Soumik Mondal; Athul Harilal; Alexander Binder (FIRE (Working Notes), 2018)

Deep One-Class Classification. - Lukas Ruff; Nico Görnitz; Lucas Deecke; Shoaib Ahmed Siddiqui; Robert A. Vandermeulen; Alexander Binder; Emmanuel Müller; Marius Kloft (ICML, 2018)

Mouse Authentication Without the Temporal Aspect - What Does a 2D-CNN Learn? - Penny Chong; Yi Xiang Marcus Tan; Juan Guarnizo; Yuval Elovici; Alexander Binder (IEEE Symposium on Security and Privacy Workshops, 2018)

Detection of Masqueraders Based on Graph Partitioning of File System Access Events. - Flavio Toffalini; Ivan Homoliak; Athul Harilal; Alexander Binder; Martín Ochoa (IEEE Symposium on Security and Privacy Workshops, 2018)

Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles. - Alexander Binder; Michael Bockmayr; Miriam Hägele; Stephan Wienert; Daniel Heim; Katharina Hellweg; Albrecht Stenzinger; Laura Parlow; Jan Budczies; Benjamin Goeppert; Denise Treue; Manato Kotani; et al. (CoRR, 2018)

An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets. - Ivan Homoliak; Dominik Breitenbacher; Alexander Binder; Pawel Szalachowski (CoRR, 2018)

Generalized PatternAttribution for Neural Networks with Sigmoid Activations. - Jiamei Sun; Alexander Binder (IJCNN, 2019)

Adversarial Attacks on Remote User Authentication Using Behavioural Mouse Dynamics. - Yi Xiang Marcus Tan; Alfonso Iacovazzi; Ivan Homoliak; Yuval Elovici; Alexander Binder (IJCNN, 2019)

BatchNorm Decomposition for Deep Neural Network Interpretation. - Lucas Y. W. Hui; Alexander Binder (IWANN (2), 2019)

Unmasking Clever Hans Predictors and Assessing What Machines Really Learn. - Sebastian Lapuschkin; Stephan Wäldchen; Alexander Binder; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (CoRR, 2019)

Resolving challenges in deep learning-based analyses of histopathological images using explanation methods. - Miriam Hägele; Philipp Seegerer; Sebastian Lapuschkin; Michael Bockmayr; Wojciech Samek; Frederick Klauschen; Klaus-Robert Müller; Alexander Binder (CoRR, 2019)

Exploring the Back Alleys: Analysing The Robustness of Alternative Neural Network Architectures against Adversarial Attacks. - Yi Xiang Marcus Tan; Yuval Elovici; Alexander Binder (CoRR, 2019)

DeepClue: Visual Interpretation of Text-Based Deep Stock Prediction. - Lei Shi 002; Zhiyang Teng; Le Wang; Yue Zhang 004; Alexander Binder (IEEE Trans. Knowl. Data Eng., 2019)

Layer-Wise Relevance Propagation: An Overview. - Grégoire Montavon; Alexander Binder; Sebastian Lapuschkin; Wojciech Samek; Klaus-Robert Müller (Explainable AI, 2019)

SmartOTPs: An Air-Gapped 2-Factor Authentication for Smart-Contract Wallets. - Ivan Homoliak; Dominik Breitenbacher; Ondrej Hujnak; Pieter H. Hartel; Alexander Binder; Pawel Szalachowski (AFT, 2020)

SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information. - Jing Yu Koh; Duc Thanh Nguyen; Quang-Trung Truong; Sai-Kit Yeung; Alexander Binder (ECCV (24), 2020)

Deep Semi-Supervised Anomaly Detection. - Lukas Ruff; Robert A. Vandermeulen; Nico Görnitz; Alexander Binder; Emmanuel Müller; Klaus-Robert Müller; Marius Kloft (ICLR, 2020)

Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. - Gary S. W. Goh; Sebastian Lapuschkin; Leander Weber; Wojciech Samek; Alexander Binder (ICPR, 2020)

Explanation-Guided Training for Cross-Domain Few-Shot Classification. - Jiamei Sun; Sebastian Lapuschkin; Wojciech Samek; Yunqing Zhao; Ngai-Man Cheung; Alexander Binder (ICPR, 2020)

Adaptive Noise Injection for Training Stochastic Student Networks from Deterministic Teachers. - Yi Xiang Marcus Tan; Yuval Elovici; Alexander Binder (ICPR, 2020)

Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification. - Penny Chong; Lukas Ruff; Marius Kloft; Alexander Binder (IJCNN, 2020)

Towards Best Practice in Explaining Neural Network Decisions with LRP. - Maximilian Kohlbrenner; Alexander Bauer 001; Shinichi Nakajima; Alexander Binder; Wojciech Samek; Sebastian Lapuschkin (IJCNN, 2020)

Understanding Image Captioning Models beyond Visualizing Attention. - Jiamei Sun; Sebastian Lapuschkin; Wojciech Samek; Alexander Binder (CoRR, 2020)

Lymphocyte counting - Error Analysis of Regression versus Bounding Box Detection Approaches. - Lin Geng Foo; Alexander Binder (CoRR, 2020)

Deja vu from the SVM Era: Example-based Explanations with Outlier Detection. - Penny Chong; Yuval Elovici; Alexander Binder (CoRR, 2020)

Detection of Adversarial Supports in Few-shot Classifiers Using Feature Preserving Autoencoders and Self-Similarity. - Yi Xiang Marcus Tan; Penny Chong; Jiamei Sun; Yuval Elovici; Alexander Binder (CoRR, 2020)

User Authentication Based on Mouse Dynamics Using Deep Neural Networks: A Comprehensive Study. - Penny Chong; Yuval Elovici; Alexander Binder (IEEE Trans. Inf. Forensics Secur., 2020)

Interpretable Deep Neural Network to Predict Estrogen Receptor Status from Haematoxylin-Eosin Images. - Philipp Seegerer; Alexander Binder; René Saitenmacher; Michael Bockmayr; Maximilian Alber; Philipp Jurmeister; Frederick Klauschen; Klaus-Robert Müller (AI and ML for Digital Pathology, 2020)

On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy. - Vignesh Srinivasan; Nils Strodthoff; Jackie Ma; Alexander Binder; Klaus-Robert Müller; Wojciech Samek (CoRR, 2021)

Towards A Conceptually Simple Defensive Approach for Few-shot classifiers Against Adversarial Support Samples. - Yi Xiang Marcus Tan; Penny Chong; Jiamei Sun; Ngai-Man Cheung; Yuval Elovici; Alexander Binder (CoRR, 2021)

Morphological and molecular breast cancer profiling through explainable machine learning. - Alexander Binder; Michael Bockmayr; Miriam Hägele; Stephan Wienert; Daniel Heim; Katharina Hellweg; Masaru Ishii; Albrecht Stenzinger; Andreas Hocke; Carsten Denkert; Klaus-Robert Müller; Frederick Klauschen (Nat. Mach. Intell., 2021)

Pruning by explaining: A novel criterion for deep neural network pruning. - Seul-Ki Yeom; Philipp Seegerer; Sebastian Lapuschkin; Alexander Binder; Simon Wiedemann; Klaus-Robert Müller; Wojciech Samek (Pattern Recognit., 2021)

Discovering Transferable Forensic Features for CNN-Generated Images Detection. - Keshigeyan Chandrasegaran; Ngoc-Trung Tran; Alexander Binder; Ngai-Man Cheung (ECCV (15), 2022)

Explain and improve: LRP-inference fine-tuning for image captioning models. - Jiamei Sun; Sebastian Lapuschkin; Wojciech Samek; Alexander Binder (Inf. Fusion, 2022)

Toward Scalable and Unified Example-Based Explanation and Outlier Detection. - Penny Chong; Ngai-Man Cheung; Yuval Elovici; Alexander Binder (IEEE Trans. Image Process., 2022)

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. - Alexander Binder; Leander Weber; Sebastian Lapuschkin; Grégoire Montavon; Klaus-Robert Müller; Wojciech Samek (CVPR, 2023)

Optimizing Explanations by Network Canonization and Hyperparameter Search. - Frederik Pahde; Galip Ümit Yolcu; Alexander Binder; Wojciech Samek; Sebastian Lapuschkin (CVPR Workshops, 2023)

Layer-wise Feedback Propagation. - Leander Weber; Jim Berend; Alexander Binder; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2023)

Beyond explaining: Opportunities and challenges of XAI-based model improvement. - Leander Weber; Sebastian Lapuschkin; Alexander Binder; Wojciech Samek (Inf. Fusion, 2023)

Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology. - Dhananjay Tomar; Alexander Binder; Andreas Kleppe (NeurIPS, 2024)

Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation. - Leander Weber; Jim Berend; Moritz Weckbecker; Alexander Binder; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (Trans. Mach. Learn. Res., 2025)

Revisiting Model Inversion Evaluation: From Misleading Standards to Reliable Privacy Assessment. - Sy-Tuyen Ho; Koh Jun Hao; Ngoc-Bao Nguyen; Alexander Binder; Ngai-Man Cheung (CoRR, 2025)