A survey on federated learning in intelligent transportation systems
The development of Intelligent Transportation System (ITS) has brought about
comprehensive urban traffic information that not only provides convenience to urban …
comprehensive urban traffic information that not only provides convenience to urban …
FDPBoost: Federated differential privacy gradient boosting decision trees
Y Li, Y Feng, Q Qian - Journal of Information Security and Applications, 2023 - Elsevier
The big data era has led to an exponential increase in data usage, resulting in significantly
advancements in data-driven domains and data mining. However, due to privacy and …
advancements in data-driven domains and data mining. However, due to privacy and …
Deep neural decision forest for acoustic scene classification
Acoustic scene classification (ASC) aims to classify an audio clip based on the characteristic
of the recording environment. In this regard, deep learning based approaches have …
of the recording environment. In this regard, deep learning based approaches have …
Federated learning for tabular data using tabnet: A vehicular use-case
W Lindskog, C Prehofer - 2022 IEEE 18th International …, 2022 - ieeexplore.ieee.org
In this paper, we show how Federated Learning (FL) can be applied to vehicular use-cases
in which we seek to classify obstacles, irregularities and pavement types on roads. Our …
in which we seek to classify obstacles, irregularities and pavement types on roads. Our …
Dealing with Data: Bringing Order to Chaos
Data is key for rapid and continuous delivery of customer value. By collecting data from
products in the field, companies in the embedded systems domain can measure and monitor …
products in the field, companies in the embedded systems domain can measure and monitor …
All data is equal or is some data more equal? On strategic data collection and use in the embedded systems domain
Effective collection and use of data is key for companies across domains and it is only
increasing in importance. For companies in the embedded systems domain, data constitutes …
increasing in importance. For companies in the embedded systems domain, data constitutes …
Applying Random Forests in Federated Learning: A Synthesis of Aggregation Techniques
Random forests (RFs) are a versatile choice for many machine learning applications.
Despite their promising efficiency and simplicity, RFs are seldom used in collaborative …
Despite their promising efficiency and simplicity, RFs are seldom used in collaborative …
[PDF][PDF] Federated Learning for Automotive Applications
W Lindskog, C Prehofer - researchgate.net
Connected vehicles provide communication and data collection from vehicles, which
enables new technology to enhance system based on usage data. In this paper, we present …
enables new technology to enhance system based on usage data. In this paper, we present …