Publications related to Protecting Circuits From Computationally Bounded And Noisy Leakage

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. Th ...

EPFL2023

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Serge Vaudenay

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

or

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Springer, Cham2020

Collaborative Sampling in Generative Adversarial Networks

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari

The standard practice in Generative Adversarial Networks (GANs) discards the discriminator during sampling. However, this sampling method loses valuable information learned by the discriminator regarding the data distribution. In this work, we propose a co ...

2020

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces

Robert Leeb, Michele Tavella

In this paper, we present and analyze an event distribution system for brain-computer interfaces. Events are commonly used to mark and describe incidents during an experiment and are therefore critical for later data analysis or immediate real-time process ...

Institute of Electrical and Electronics Engineers2017

Computation of a 768-Bit Prime Field Discrete Logarithm

Arjen Lenstra, Thorsten Kleinjung

This paper reports on the number field sieve computation of a 768-bit prime field discrete logarithm, describes the different parameter optimizations and resulting algorithmic changes compared to the factorization of a 768-bit RSA modulus, and briefly disc ...

Springer International Publishing Ag2017

Compressive Spectral Clustering

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy, Nicolas Tremblay

Spectral clustering has become a popular technique due to its high performance in many contexts. It comprises three main steps: create a similarity graph between N objects to cluster, compute the first k eigenvectors of its Laplacian matrix to define a fea ...

2016

Dimensionality Reduction in Dynamic Optimization under Uncertainty

Napat Rujeerapaiboon

Dynamic optimization problems affected by uncertainty are ubiquitous in many application domains. Decision makers typically model the uncertainty through random variables governed by a probability distribution. If the distribution is precisely known, then ...

EPFL2016

MATHICSE Technical Report : Fast computation of the matrix exponential for a Toeplitz matrix

Daniel Kressner, Robert Gerhard Jérôme Luce

The computation of the matrix exponential is a ubiquitous operation in numerical mathematics, and for a general, unstructured n×n matrix it can be computed in O(n3) operations. An interesting problem arises if the input matrix is a Toeplitz matrix, for exa ...

MATHICSE2016

Compressed Sensing of Memoryless Sources

Saeid Haghighatshoar

Compressed sensing is a new trend in signal processing for efficient sampling and signal acquisition. The idea is that most real-world signals have a sparse representation in an appropriate basis and this can be exploited to capture the sparse signal by ta ...

EPFL2014

FID-guided retrospective motion correction based on autofocusing

Rolf Gruetter, Tobias Kober, Cristina Granziera, Gunnar Krüger

This work investigates the possibility of using FID navigator signals to improve the performance of a recently proposed autofocusing-based retrospective motion correction technique. FID navigators were incorporated into an MP-RAGE sequence and 3 subjects w ...

2014

Protecting Circuits From Computationally Bounded And Noisy Leakage

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Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Collaborative Sampling in Generative Adversarial Networks

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces

Computation of a 768-Bit Prime Field Discrete Logarithm

Compressive Spectral Clustering

Dimensionality Reduction in Dynamic Optimization under Uncertainty

MATHICSE Technical Report : Fast computation of the matrix exponential for a Toeplitz matrix

Compressed Sensing of Memoryless Sources

FID-guided retrospective motion correction based on autofocusing

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Collaborative Sampling in Generative Adversarial Networks

TiD-Introducing and Benchmarking an Event-Delivery System for Brain-Computer Interfaces

Computation of a 768-Bit Prime Field Discrete Logarithm

Compressive Spectral Clustering

Dimensionality Reduction in Dynamic Optimization under Uncertainty

FID-guided retrospective motion correction based on autofocusing

MATHICSE Technical Report : Fast computation of the matrix exponential for a Toeplitz matrix

Compressed Sensing of Memoryless Sources