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Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

Publications associées (28)

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

Touradj Ebrahimi, Michela Testolina, Davi Nachtigall Lazzarotto

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

Springer2024

In-Sensor Passive Speech Classification with Phononic Metamaterials

Luis Guillermo Villanueva Torrijo, Daniel Moreno Garcia

Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their u ...

Wiley-V C H Verlag Gmbh2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Alexander Carl Unnervik

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Daniel Kressner, Alice Cortinovis

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

Siam Publications2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Gibbs sampling the posterior of neural networks

Lenka Zdeborová, Emanuele Troiani, Giovanni Piccioli

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Iop Publishing Ltd2024

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at √sNN=5.02 TeV

Matthias Finger, Konstantin Androsov, Qian Wang, Jan Steggemann, Yiming Li, Anna Mascellani, Varun Sharma, Xin Chen, Rakesh Chawla, Matteo Galli

Two -particle Bose-Einstein momentum correlation functions are studied for charged-hadron pairs in lead -lead collisions at a center -of -mass energy per nucleon pair of .'/sNN = 5.02 TeV. The data sample, containing 4.27 x 109 minimum bias events correspo ...

Amer Physical Soc2024

How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study

Wendy Lee Queen, Jocelyn Richard Roth, Rawan Al Natour

Metal-organic frameworks (MOFs) are a rapidly growing class of materials that offer great promise in various applications. However, the synthesis remains challenging: for example, a range of crystal structures can often be accessed from the same building b ...

Wiley-V C H Verlag Gmbh2024

Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

In-Sensor Passive Speech Classification with Phononic Metamaterials

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Gibbs sampling the posterior of neural networks

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at √sNN=5.02 TeV

How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study

Graph Chatbot

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

In-Sensor Passive Speech Classification with Phononic Metamaterials

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Gibbs sampling the posterior of neural networks

Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at √sNN=5.02 TeV

How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study

Graph generative deep learning models with an application to circuit topologies

Graph generative deep learning models with an application to circuit topologies