A multiple birthday attack on NTRU

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The SALUTE project aims at evaluating performance of electroacoustic metasurface, employing a surface array of controlled electroacoustic actuators, for smart acoustic lining under grazing turbulent flow to be used in UHBR Technologies Engines. Theoretical ...

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 ...

This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication structure corresponding to a hypergraph, by which complex relationships between ...

A near collision attack against the Grain v1 stream cipher was proposed by Zhang et al. in Eurocrypt 18. The attack uses the fact that two internal states of the stream cipher with very low hamming distance between them, produce similar keystream sequences ...

We study the computational complexity of the optimal transport problem that evaluates the Wasser- stein distance between the distributions of two K-dimensional discrete random vectors. The best known algorithms for this problem run in polynomial time in th ...

A shift from fossil-based energy and products to more sustainable alternatives is essential to reduce greenhouse gas emissions and associated climate change impacts. Biomass represents a promising alternative for providing fuels and carbon-based products w ...

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

This work presents a graph neural network (GNN) framework for solving the maximum independent set (MIS) problem, inspired by dynamic programming (DP). Specifically, given a graph, we propose a DP-like recursive algorithm based on GNNs that firstly construc ...

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 ...

The problem of learning graphons has attracted considerable attention across several scientific communities, with significant progress over the re-cent years in sparser regimes. Yet, the current techniques still require diverg-ing degrees in order to succe ...

Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

Objective. This study aims to design and implement the first deep learning (DL) model to classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state electroencephalographic (EEG) signals. Approach. EEG recordings of 17 heal ...

A multiple birthday attack on NTRU

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Smart acoustic lining for UHBR technologies engine: from the design of an electroacoustic metasurface to experimental characterization under flow

Approximation Algorithms for Allocation and Network Design

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Near Collision Attack Against Grain V1

Discrete Optimal Transport with Independent Marginals is #P-Hard

Decision support for the design of integrated biorefineries

Evaluating the effect of sparse convolutions on point cloud compression

Maximum Independent Set: Self-Training through Dynamic Programming

Robust Collaborative Learning with Linear Gradient Overhead

Learning Sparse Graphons And The Generalized Kesten-Stigum Threshold

Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG