EVENTS
COMING SOON :)
Edge Intelligence is a research program of the MIAI institute that works on efficient resource management and distributed/federated Machine Learning. For instance, we promote locally distributed computations related to AI to avoid the waste of energy lost during data transfers. Thanks to a small data center close to the edge of the network, data produced on mobile devices can be pre-computed in low latency networks. Further computations may then be executed on a regular data center over the Cloud.
Distribute the computation for better efficiency. (E.g. computing power, workload, storage management)
Collaborate with the intent to keep the data of each agent heterogeneous, local, and private. Federated learning can be centralized, decentralized, and semi-centralized.
Efficient allocation and execution of the tasks in the appropriate heterogeneous and dynamic distributed computing devices connected at the edge level.
Predict better for future data. In online settings, data becomes available in sequential order.
Optimization, Distributed scheduling
Distributed scheduling, IoT
Resource Management, Federated Learning
Infrastructure for the Edge
Optimization, Federated Learning
System for edge computing
IoT
Multi-agent AI
Pervasive FL
Scheduling
Pervasive FL
System for edge computing
Scheduling, Frugal methods
Atos / Eviden, HPC
Adeunis, IoT sensors
Ryax Technologies, serverless edge-cloud
Orange, computer vision
UGA and ENS Lyon, energy consumption
UGA, combinatorial optimization
CEA, neural networks
UGA, decentralized learning algorithms
Atos / Eviden, scheduling and energy consumption
Berger-Levrault, edge processing
COMING SOON :)
