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Matthias Reisser
Matthias Reisser
Qualcomm AI Research
Verified email at qti.qualcomm.com
Title
Cited by
Cited by
Year
Relaxed quantization for discretized neural networks
C Louizos, M Reisser, T Blankevoort, E Gavves, M Welling
arXiv preprint arXiv:1810.01875, 2018
2122018
Federated mixture of experts
M Reisser, C Louizos, E Gavves, M Welling
arXiv preprint arXiv:2107.06724, 2021
182021
Quantization robust federated learning for efficient inference on heterogeneous devices
K Gupta, M Fournarakis, M Reisser, C Louizos, M Nagel
arXiv preprint arXiv:2206.10844, 2022
162022
Dp-rec: Private & communication-efficient federated learning
A Triastcyn, M Reisser, C Louizos
arXiv preprint arXiv:2111.05454, 2021
162021
An expectation-maximization perspective on federated learning
C Louizos, M Reisser, J Soriaga, M Welling
arXiv preprint arXiv:2111.10192, 2021
132021
Hyperparameter optimization through neural network partitioning
B Mlodozeniec, M Reisser, C Louizos
arXiv preprint arXiv:2304.14766, 2023
62023
Decentralized learning with random walks and communication-efficient adaptive optimization
A Triastcyn, M Reisser, C Louizos
Workshop on Federated Learning: Recent Advances and New Challenges (in …, 2022
62022
Variance propagation for quantization
M Reisser, M Welling, E Gavves, C Louizos
US Patent App. 16/417,430, 2019
42019
Joint pruning and quantization scheme for deep neural networks
Y Lu, Y Wang, TPF Blankevoort, C Louizos, M Reisser, J Hou
US Patent App. 17/030,315, 2021
32021
Federated averaging as expectation maximization
C Louizos, M Reisser, J Soriaga, M Welling
32021
Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data
M Morafah, M Reisser, B Lin, C Louizos
arXiv preprint arXiv:2405.07925, 2024
22024
Systems and methods for modifying neural networks for binary processing applications
M Reisser, SK Pitre, X Zhu, EH Teague, Z Wang, M Welling
US Patent 11,790,241, 2023
22023
Federated mixture models
M Reisser, M Welling, E Gavves, C Louizos
US Patent App. 17/756,957, 2023
22023
A Mutual Information Perspective on Federated Contrastive Learning
C Louizos, M Reisser, D Korzhenkov
arXiv preprint arXiv:2405.02081, 2024
12024
Federated Learning Toolkit with Voice-based User Verification Demo
P Mandke, R Oberst, M Reisser, A Chakraborty, C Louizos, J Soriaga, ...
Proceedings of INTERSPEECH 2023, 2023
12023
Federated Functional Variational Inference
M Hutchinson, M Reisser, C Louizos
Proceedings of the NeurIPS 2021 worksop on Bayesian Deep Learning, 2021
12021
Deep Learning for Compute in Memory
M Reisser, S Pitre, X Zhu, H Teague, J Wang, M Welling
Research Symposium on Tiny Machine Learning, 2020
12020
Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
W Cho, S Choi, D Das, M Reisser, T Kim, S Yun, F Porikli
arXiv preprint arXiv:2411.01179, 2024
2024
BI-DIRECTIONAL COMPRESSION AND PRIVACY FOR EFFICIENT COMMUNICATION IN FEDERATED LEARNING
M Reisser, A Triastcyn, C Louizos
US Patent App. 18/556,622, 2024
2024
Sparsity-inducing federated machine learning
C Louizos, H Hosseini, M Reisser, M Welling, JB Soriaga
US Patent App. 18/040,111, 2023
2023
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