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2020 – today
- 2024
[c7]Christos Louizos, Matthias Reisser, Denis Korzhenkov:
A Mutual Information Perspective on Federated Contrastive Learning. ICLR 2024- [i9]Christos Louizos, Matthias Reisser, Denis Korzhenkov:
A Mutual Information Perspective on Federated Contrastive Learning. CoRR abs/2405.02081 (2024) - [i8]Mahdi Morafah, Matthias Reisser, Bill Lin, Christos Louizos:
Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data. CoRR abs/2405.07925 (2024) - [i7]Wonguk Cho, Seokeon Choi, Debasmit Das, Matthias Reisser, Taesup Kim, Sungrack Yun, Fatih Porikli:
Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models. CoRR abs/2411.01179 (2024) - 2023
- [j1]Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel:
Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Bruno Mlodozeniec, Matthias Reisser, Christos Louizos:
Hyperparameter Optimization through Neural Network Partitioning. ICLR 2023 - [c5]Prathamesh Mandke, Rachel Oberst, Matthias Reisser, Avijit Chakraborty, Christos Louizos, Joseph Soriaga, Daniel Madrigal Diaz, Andre Manoel, Nalin Singal, Jeff Omhover, Robert Sim:
Federated Learning Toolkit with Voice-based User Verification Demo. INTERSPEECH 2023: 5263-5264 - [i6]Bruno Mlodozeniec, Matthias Reisser, Christos Louizos:
Hyperparameter Optimization through Neural Network Partitioning. CoRR abs/2304.14766 (2023) - 2022
- [i5]Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel:
Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices. CoRR abs/2206.10844 (2022) - 2021
- [i4]Matthias Reisser, Christos Louizos, Efstratios Gavves, Max Welling:
Federated Mixture of Experts. CoRR abs/2107.06724 (2021) - [i3]Aleksei Triastcyn, Matthias Reisser, Christos Louizos:
DP-REC: Private & Communication-Efficient Federated Learning. CoRR abs/2111.05454 (2021) - [i2]Christos Louizos, Matthias Reisser, Joseph Soriaga, Max Welling:
An Expectation-Maximization Perspective on Federated Learning. CoRR abs/2111.10192 (2021)
2010 – 2019
- 2019
- [c4]Diede Rusticus, Lutz Goldmann, Matthias Reisser, Mauricio Villegas
:
Document Domain Adaptation with Generative Adversarial Networks. ICDAR 2019: 1432-1437 - [c3]Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling:
Relaxed Quantization for Discretized Neural Networks. ICLR (Poster) 2019 - 2018
- [c2]Peter O'Connor, Efstratios Gavves, Matthias Reisser, Max Welling:
Temporally Efficient Deep Learning with Spikes. ICLR (Poster) 2018 - [i1]Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling:
Relaxed Quantization for Discretized Neural Networks. CoRR abs/1810.01875 (2018) - 2016
- [c1]Katerina Shapoval, Matthias Reisser, Johannes Baldinger:
Using Hidden Markov Models for Descriptive and Predictive Analysis of Purchasing Histories. MKWI 2016: 1245-1256
Coauthor Index
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last updated on 2024-12-12 21:56 CET by the dblp team
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