Publications associées à On Optimal Replication Group Splits in P2P Data Stores Based on the Hypercube

Automated Formal Verification of Software Network Functions

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

EPFL2024

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Along with the successful deployment of deep neural networks in several application domains, the need to unravel the black-box nature of these networks has seen a significant increase recently. Several methods have been introduced to provide insight into t ...

Assoc Computational Linguistics-Acl2023

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TAYLOR & FRANCIS INC2023

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Peer-to-peer (p2p) networks are not independent of their peers, and the network efficiency depends on peers contributing resources. Because shared resources are not free, this contribution must be rewarded. Peers across the network may share computation po ...

IEEE COMPUTER SOC2022

Automated Verification of Network Function Binaries

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Formally verifying the correctness of software network functions (NFs) is necessary for network reliability, yet existing techniques require full source code and mandate the use of specific data structures. We describe an automated technique to verify NF b ...

USENIX Association2022

Detecting Latent Training Needs Using Large Datasets

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In today's world, there is no shortage of disruptors acting on various professional domains. The Fourth Industrial Revolution, with its AI-driven and automation-focused technologies, has fundamentally changed many domains -- particularly the Information an ...

EPFL2022

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Multi-scale and multi-patch deep models have been shown effective in removing blurs of dynamic scenes. However, these methods still suffer from one major obstacle: manually designing a lightweight and high-efficiency network is challenging and time-consumi ...

IEEE2021

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Karl Aberer, Quoc Viet Hung Nguyen, Zoltán Miklós, Thành Tâm Nguyên

Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and ele ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Universal Adversarial Attacks on Text Classifiers

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Despite the vast success neural networks have achieved in different application domains, they have been proven to be vulnerable to adversarial perturbations (small changes in the input), which lead them to produce the wrong output. In this paper, we propos ...

IEEE2019

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Emmanouil Koukoutos

Program synthesis was first proposed a few decades ago, but in the last decade it has gained increased momentum in the research community. The increasing complexity of software has dictated the urgent need for improved supporting tools that verify the soft ...

EPFL2019

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The task of Heterogeneous Face Recognition consists in matching face images that are sensed in different domains, such as sketches to photographs (visual spectra images), thermal images to photographs or near-infrared images to photographs. In this work we ...

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Verifying Software Network Functions with No Verification Expertise

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ACM2019

Macroecology in the age of Big Data - Where to go from here?

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USENIX Association2018

Log-Free Concurrent Data Structures

Rachid Guerraoui, Aleksandar Dragojevic, Mihail Igor Zablotchi, Tudor Alexandru David

Non-volatile RAM (NVRAM) makes it possible for data structures to tolerate transient failures, assuming however that programmers have designed these structures such that their consistency is preserved upon recovery. Previous approaches are typically transa ...

USENIX ASSOC2018

Graph learning under sparsity priors

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Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the application domain. ...

Ieee2017

On verifying causal consistency

Rachid Guerraoui, Jad Hamza

Causal consistency is one of the most adopted consistency criteria for distributed implementations of data structures. It ensures that operations are executed at all sites according to their causal precedence. We address the issue of verifying automaticall ...

Hyperdimensional computing for blind and one-shot classification of EEG error-related potentials

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The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as “hypervectors,” is a brain-inspired alternative to computing with numbers. HD computing ...

Springer Verlag2020