Publications

1. Ultra-Lightweight Adaptive Bitrate Deep Video Compression
   A. Hojjat, J. Haberer, O. Landsiedel
   IJCV: International Journal of Computer Vision, Volume 134
   (extended version of [5] MCUCoder)
   Published Version | GitHub

2. Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment
   J. Haberer, J.E. Wilhelm, O. Landsiedel
   Mobile AI Workshop and Associated Challenges, 6th edition, at CVPR'26 Published Version | arXiv | GitHub

3. ThinkingViT: Matryoshka Thinking Vision Transformer for Elastic Inference
   A. Hojjat, J. Haberer, S. Pirk, O. Landsiedel
   CVPR'26: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition & ES-FoMo III: 3rd Workshop on Efficient Systems for Foundation Models, ICML'25
   Published Version (CVPR) | OpenReview (ES-FoMo III) | arXiv | GitHub

4. HydraViT: Stacking Heads for a Scalable ViT
   J. Haberer, A. Hojjat, O. Landsiedel
   NeurIPS'24: Advances in Neural Information Processing Systems 37
   Published Version | OpenReview | arXiv | GitHub

5. MCUCoder: Adaptive Bitrate Learned Video Compression for IoT Devices (Best Paper Honorable Mention)
   A. Hojjat, J. Haberer, O. Landsiedel
   DAGM GCPR'25: German Conference on Pattern Recognition & Workshop on Machine Learning and Compression, NeurIPS'24
   Published Version (GCPR) | OpenReview (NeurIPS Workshop) | arXiv | GitHub

6. MatchCurv: Communication-Efficient Decentralized Federated Learning in Heterogeneous Environments (Best Presentation Award)
   H.P. Dussa, J. Haberer, O. Landsiedel
   1st Workshop on Enabling Machine Learning Operations for next-Gen Embedded Wireless Networked Devices, EWSN'24
   Published Version | GitHub

7. LimitNet: Progressive, Content-Aware Image Offloading for Extremely Weak Devices & Networks
   A. Hojjat, J. Haberer, T. Zainab, O. Landsiedel
   MobiSys'24: Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services
   Published Version | arXiv | GitHub

8. Machine Learning with Computer Networks: Techniques, Datasets and Models
   A. Haitham, S. Pochaba, A. Boltres, D. Laniewski, J. Haberer, P. Leonard, R. Poorzare, D. Stolpmann, N. Wehner, A. Redder, E. Samikwa, M. Seufert
   IEEE Access, 2024
   Published Version

9. ProgDTD: Progressive Learned Image Compression with Double-tail-drop Training
   A. Hojjat, J. Haberer, O. Landsiedel
   New Trends in Image Restoration and Enhancement Workshop, at CVPR'23
   Published Version | arXiv | GitHub

10. Activation Sparsity and Dynamic Pruning for Split Computing in Edge AI
    J. Haberer, O. Landsiedel
    3rd International Workshop on Distributed Machine Learning, at CoNEXT'22
    Published Version