Publications associées (32)

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Joshua Alexander Harrison Klein

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...
EPFL2024

HEEPocrates: An Ultra-Low-Power RISC-V Microcontroller for Edge-Computing Healthcare Applications

David Atienza Alonso, Alexandre Sébastien Julien Levisse, Miguel Peon Quiros, Simone Machetti, Pasquale Davide Schiavone

The field of edge computing in healthcare has seen remarkable growth due to the increasing demand for real-time processing of data in applications. However, challenges persist due to limitations in healthcare devices' performance and power efficiency. To o ...
Europractice2024

Towards General-Purpose Decentralized Computing with Permissionless Extensibility

Enis Ceyhun Alp

Smart contracts have emerged as the most promising foundations for applications of the blockchain technology. Even though smart contracts are expected to serve as the backbone of the next-generation web, they have several limitations that hinder their wide ...
EPFL2024

GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation

Daniel Gatica-Perez, Sina Sajadmanesh

In this paper, we study the problem of learning Graph Neural Networks (GNNs) with Differential Privacy (DP). We propose a novel differentially private GNN based on Aggregation Perturbation (GAP), which adds stochastic noise to the GNN's aggregation functio ...
Berkeley2023

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