← Authors

Alexander Binder

13 papers · 2010–2024 · 8 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (5) 🗺️ Taxonomy Completionist (22) 🐣 Hot Topic Early Bird 🏃 Academic Marathon (14) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (8) 🌱 Topic Pioneer 💎 Century Club (13) 🚀 Conference Pioneer 📈 Trend Setter ❓ The Questioner

Conferences

ECCV (3) CVPR (2) JMLR (2) NIPS (2) ACML (1) AISTATS (1) ICLR (1) ICML (1)

Top co-authors

Marius Kloft (5) Klaus-Robert Müller (4) Wojciech Samek (3) Sebastian Lapuschkin (3) Grégoire Montavon (3) Yunwen Lei (2) Duc Thanh Nguyen (2) Nico Görnitz (2) Quang-Trung Truong (2) Emmanuel Müller (2)

Research topics

Computer Vision (1)

Keywords

support vector machine (2) layer-wise relevance propagation (2) support vector data description (2) multiple kernel learning (2) neural network (2) feature attribution (1) explainable ai (1) domain generalization (1) reproducing kernel hilbert space (1) label noise (1) large-scale learning (1) linear discriminant analysis (1) multi-class classification (1) convex optimization (1) one-class svm (1) brain-computer interface (1) cluster structure (1) generalization error bound (1) hidden markov model (1) eeg signal processing (1)

Papers

Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology NIPS 2024
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations CVPR 2023
Discovering Transferable Forensic Features for CNN-Generated Images Detection ECCV 2022
Deep Semi-Supervised Anomaly Detection ICLR 2020
SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information ECCV 2020
Deep One-Class Classification ICML 2018
Urban Zoning Using Higher-Order Markov Random Fields on Multi-View Imagery Data ECCV 2018
The LRP Toolbox for Artificial Neural Networks JMLR 2016
Localized Multiple Kernel Learning—A Convex Approach ACML 2016
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks CVPR 2016
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms NIPS 2015
Learning and Evaluation in Presence of Non-i.i.d. Label Noise AISTATS 2014
The SHOGUN Machine Learning Toolbox JMLR 2010