Edvin Listo Zec

edvin listo zec

senior ml engineer, phd

research

publications

complete list on google scholar.

2026
overcoming label shift in target-aware federated learning
e. listo zec, a. breitholtz, f.d. johansson · transactions on machine learning research (tmlr) · [bibtex]
2025
on the effects of similarity metrics in decentralized deep learning under distributional shift
e. listo zec, t. hagander, e. ihre-thomason, s. girdzijauskas · transactions on machine learning research (tmlr) · [bibtex]
2024
efficient node selection in private personalized decentralized learning
e. listo zec, j. östman, o. mogren, d. gillblad · northern lights deep learning conference · PMLR
2023
concept-aware clustering for decentralized deep learning under temporal shift
m. toftås, e. klefbom, e. listo zec, m. willbo, o. mogren · icml workshop on federated learning and analytics in practice · [bibtex]
2023
federated learning for performance prediction in multi-operator environments
x. lan, j. taghia, f. moradi, m.a. khoshkholghi, e. listo zec, o. mogren, t. mahmoodi, a. johnsson · ITU journal on future and evolving technologies
2022
effgan: ensembles of fine-tuned federated gans
e. ekblom, e. listo zec, o. mogren · ieee international conference on big data · [bibtex]
2022
residual value prediction using deep learning
e. listo zec, o. mogren, a.c. mellquist, s. fallahi, p. algurén · ieee international conference on big data · [bibtex]
2022
decentralized adaptive clustering of deep nets is beneficial for client collaboration
e. listo zec, e. ekblom, m. willbo, o. mogren, s. girdzijauskas · fl-ijcai'22 · [bibtex]
2022
adaptive expert models for personalization in federated learning
m. isaksson, e. listo zec, r. cöster, d. gillblad, s. girdzijauskas · fl-ijcai'22 · [bibtex]
2021
decentralized federated learning of deep neural networks on non-iid data
n. onoszko, g. karlsson, o. mogren, e. listo zec · workshop on federated learning for user privacy and data confidentiality, icml · [bibtex]
2021
scaling federated learning for fine-tuning of large language models
a. hilmkil, s. callh, m. barbieri, l.r. sütfeld, e. listo zec, o. mogren · international conference on applications of natural language to information systems (NLDB)
2020
specialized federated learning using a mixture of experts
e. listo zec, j. martinsson, o. mogren, l.r. sütfeld, d. gillblad · arxiv preprint · [bibtex]
2020
adversarial representation learning for private speech generation
d. ericsson, a. östberg, e. listo zec, j. martinsson, o. mogren · workshop on self-supervision in audio and speech, icml · [bibtex]
2020
adversarial representation learning for synthetic replacement of private attributes
j. martinsson, e. listo zec, d. gillblad, o. mogren · arxiv preprint · [bibtex]
2019
recurrent conditional generative adversarial networks for autonomous driving sensor modelling
h. arnelid, e. listo zec, n. mohammadiha · ieee itsc · [bibtex]
2019
grammatical gender in swedish is predictable using recurrent neural networks
e. listo zec, o. mogren · proceedings of the 15th swecog conference
2019
recurrent conditional gans for time series sensor modelling
e. listo zec, h. arnelid, n. mohammadiha · icml time series workshop
2018
statistical sensor modelling for autonomous driving using autoregressive input-output hmms
e. listo zec, n. mohammadiha, a. schliep · ieee itsc · [bibtex]
2017
probabilistic modelling of sensors in autonomous vehicles
e. listo zec · msc thesis, chalmers university of technology

students

interested in a master thesis on deep learning? feel free to reach out — i always take time to discuss ideas. some topic areas: federated and decentralized learning · out-of-distribution generalization · deep learning for climate and sustainability · deep learning for understanding social issues.

2024
with a little help from my friends — a comparative study of decentralized deep learning strategies
tom hagander and eric ihre-thomason · lund university
2023
decentralized deep learning under distributed concept drift
emilie klefbom and marcus toftås · chalmers university of technology
2022
impact of model architecture and data distribution on self-supervised federated learning
karin bergdahl · lund university
2021
pens: leveraging data heterogeneity in federated learning
noa onoszko and gustav karlsson · chalmers university of technology
2020
adversarial representation learning for private speech generation
david ericsson and adam östberg · chalmers university of technology
2018
sensor modelling with recurrent conditional gans
henrik arnelid · chalmers university of technology