Publications related to On Tracking Freeriders in Gossip Protocols

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Carmela González Troncoso, Bogdan Kulynych

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

New York2023

Gradient-based optimisation of the conditional-value-at-risk using the multi-level Monte Carlo method

Fabio Nobile, Sundar Subramaniam Ganesh

In this work, we tackle the problem of minimising the Conditional-Value-at-Risk (CVaR) of output quantities of complex differential models with random input data, using gradient-based approaches in combination with the Multi-Level Monte Carlo (MLMC) method ...

2022

Optimal Matching of Random Parts

Thomas Alois Weber

This paper examines the minimization of the cost for an expected random production output, given an assembly of finished goods from two random inputs, matched in two categories. We describe the optimal input portfolio, first using the standard normal appro ...

2022

Certification of the efficient random number generation technique based on single-photon detector arrays and time-to-digital converters

Edoardo Charbon, Samuel Burri

True random number generators (TRNGs) allow the generation of true random bit sequences, guaranteeing the unpredictability and perfect balancing of the generated values. TRNGs can be realised from the sampling of quantum phenomena, for instance, the detect ...

Hoboken2021

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

Edoardo Charbon, Claudio Bruschini, Ivan Michel Antolovic, Mario Stipcevic

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

SPIE2021

A Structure Theorem for Level Sets of Multiplicative Functions and Applications

Florian Karl Richter

Given a level set E of an arbitrary multiplicative function f, we establish, by building on the fundamental work of Frantzikinakis and Host [14, 15], a structure theorem that gives a decomposition of

1_{E}

into an almost periodic and a pseudo-random part ...

2020

Deterministic Algorithms for Submodular Maximization Problems

Moran Feldman

Randomization is a fundamental tool used in many theoretical and practical areas of computer science. We study here the role of randomization in the area of submodular function maximization. In this area, most algorithms are randomized, and in almost all c ...

ASSOC COMPUTING MACHINERY2018

Asynchronous adaptive networks

Ali H. Sayed

In a recent article [1] we surveyed advances related to adaptation, learning, and optimization over synchronous networks. Various distributed strategies were discussed that enable a collection of networked agents to interact locally in response to streamin ...

Elsevier2018

Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations

Alfio Quarteroni, Gianluigi Rozza, Peng Chen

In this paper we develop and analyze a multilevel weighted reduced basis method for solving stochastic optimal control problems constrained by Stokes equations. We prove the analytic regularity of the optimal solution in the probability space under certain ...

Springer Heidelberg2016

MATHICSE Technical Report : Dimensionality reduction of parameter-dependent problems through proper orthogonal decomposition

Alfio Quarteroni, Andrea Manzoni, Federico Negri

The numerical solution of partial differential equations (PDEs) depending on para- metrized or random input data is computationally intensive. Reduced order modeling techniques, such as the reduced basis methods, have been developed to alleviate this compu ...

MATHICSE2016

On Tracking Freeriders in Gossip Protocols

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Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Gradient-based optimisation of the conditional-value-at-risk using the multi-level Monte Carlo method

Optimal Matching of Random Parts

Certification of the efficient random number generation technique based on single-photon detector arrays and time-to-digital converters

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

A Structure Theorem for Level Sets of Multiplicative Functions and Applications

Deterministic Algorithms for Submodular Maximization Problems

Asynchronous adaptive networks

Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations

MATHICSE Technical Report : Dimensionality reduction of parameter-dependent problems through proper orthogonal decomposition

Certification of the efficient random number generation technique based on single-photon detector arrays and time-to-digital converters

Gradient-based optimisation of the conditional-value-at-risk using the multi-level Monte Carlo method

Optimal Matching of Random Parts

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Deterministic Algorithms for Submodular Maximization Problems

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations

A Structure Theorem for Level Sets of Multiplicative Functions and Applications

MATHICSE Technical Report : Dimensionality reduction of parameter-dependent problems through proper orthogonal decomposition

Asynchronous adaptive networks