Publication

Permutation-based Decoding of Reed-Muller Codes in Binary Erasure Channel

Publications associées (31)

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

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Low Power LDPC Decoding by Reliable Voltage Down-Scaling

Andreas Peter Burg

Low-Density Parity-Check (LDPC) decoder is among the power hungry building blocks of wireless communication systems. Voltage scaling down to Near-Threshold (NT) voltages substantially improves energy efficiency, in theory up 10x. However, tuning the voltag ...

IEEE2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Results on Sparse Integer Programming and Geometric Independent Sets

Jana Tabea Cslovjecsek

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

EPFL2023

Approximation Algorithms for Allocation and Network Design

Etienne Michel François Bamas

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

EPFL2023

Latency Interfaces for Systems Code

Rishabh Ramesh Iyer

This thesis demonstrates that it is feasible for systems code to expose a latency interface that describes its latency and related side effects for all inputs, just like the code's semantic interface describes its functionality and related side effects. S ...

EPFL2023

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Yunus Inan

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

EPFL2023

On the (Im)possibility of Commitment over Gaussian Unfair Noisy Channels

Commitment is a key primitive which resides at the heart of several cryptographic protocols. Noisy channels can help realize information-theoretically secure commitment schemes; however, their imprecise statistical characterization can severely impair such ...

2023

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, John Stephan, Sadegh Farhadkhani, Le Nguyen Hoang, Nirupam Gupta, Rafaël Benjamin Pinot

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023