2025
Re-interpreting rules interpretability.
Int. J. Data Sci. Anal., June, 2025
Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries.
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Comput. Methods Programs Biomed., 2025
Federated Binary Matrix Factorization Using Proximal Optimization.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
Little Is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
Landscaping Linear Mode Connectivity.
CoRR, 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective.
CoRR, 2024
Visual Computing for Autonomous Driving.
IEEE Computer Graphics and Applications, 2024
Layer-wise linear mode connectivity.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
When, Where and How Does it Fail? A Spatial-Temporal Visual Analytics Approach for Interpretable Object Detection in Autonomous Driving.
IEEE Trans. Vis. Comput. Graph., December, 2023
Open-source skull reconstruction with MONAI.
SoftwareX, July, 2023
Protecting Sensitive Data through Federated Co-Training.
CoRR, 2023
FAM: Relative Flatness Aware Minimization.
Proceedings of the Topological, 2023
Federated Learning from Small Datasets.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Nothing but Regrets - Privacy-Preserving Federated Causal Discovery.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Regret-based Federated Causal Discovery.
Proceedings of the KDD'22 Workshop on Causal Discovery, 15 August 2022, Washington DC, USA, 2022
2021
TsmoBN: Interventional Generalization for Unseen Clients in Federated Learning.
CoRR, 2021
Novelty Detection in Sequential Data by Informed Clustering and Modeling.
CoRR, 2021
Approaches to Uncertainty Quantification in Federated Deep Learning.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021
Relative Flatness and Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization.
Proceedings of the 9th International Conference on Learning Representations, 2021
Third International Workshop on Data-Centric Dependability and Security (DCDS).
Proceedings of the 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2021
2020
Feature-Robustness, Flatness and Generalization Error for Deep Neural Networks.
CoRR, 2020
Resource-Constrained On-Device Learning by Dynamic Averaging.
Proceedings of the ECML PKDD 2020 Workshops, 2020
HOPS: Probabilistic Subtree Mining for Small and Large Graphs.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Second International Workshop on Data-Centric Dependability and Security (DCDS).
Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2020
2019
Black-Box Parallelization for Machine Learning.
PhD thesis, 2019
A Reparameterization-Invariant Flatness Measure for Deep Neural Networks.
CoRR, 2019
Adaptive Communication Bounds for Distributed Online Learning.
CoRR, 2019
Information-Theoretic Perspective of Federated Learning.
CoRR, 2019
System Misuse Detection Via Informed Behavior Clustering and Modeling.
Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2019
2018
Corresponding Projections for Orphan Screening.
CoRR, 2018
Efficient Decentralized Deep Learning by Dynamic Model Averaging.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018
2017
Issues in complex event processing: Status and prospects in the Big Data era.
J. Syst. Softw., 2017
Co-Regularised Support Vector Regression.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017
Effective Parallelisation for Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
2016
Communication-Efficient Distributed Online Learning with Kernels.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016
Ligand-Based Virtual Screening with Co-regularised Support Vector Regression.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016
2014
Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014
2013
Communication-Efficient Distributed Online Prediction using Dynamic Model Synchronizations.
Proceedings of the First International Workshop on Big Dynamic Distributed Data, 2013
Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013
Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013