Publications related to Hypercomputation

Related publications (28)

Low-Rank Tensor Approximations for Solving Multimarginal Optimal Transport Problems\ast

Daniel Kressner, Christoph Max Strössner

By the addition of entropic regularization, multimarginal optimal transport problems can be trans-formed into tensor scaling problems, which can be solved numerically using the multimarginal Sinkhorn algorithm. The main computational bottleneck of this alg ...

SIAM PUBLICATIONS2023

A mixed precision LOBPCG algorithm

Daniel Kressner, Meiyue Shao

The locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm is a popular approach for computing a few smallest eigenvalues and the corresponding eigenvectors of a large Hermitian positive definite matrix A. In this work, we propose a mix ...

SPRINGER2023

Accelerated deep self-supervised ptycho-laminography for three-dimensional nanoscale imaging of integrated circuits

Manuel Guizar Sicairos, Yi Jiang

Three-dimensional inspection of nanostructures such as integrated circuits is important for security and reliability assurance. Two scanning operations are required: ptychographic to recover the complex transmissivity of the specimen, and rotation of the s ...

2023

Training Efficient Controllers via Analytic Policy Gradient

Dario Floreano, Davide Scaramuzza, Valentin Wüest

Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

New York2023

On Succinct Non-interactive Arguments in Relativized Worlds

Alessandro Chiesa

Succinct non-interactive arguments of knowledge (SNARKs) are cryptographic proofs with strong efficiency properties. Applications of SNARKs often involve proving computations that include the SNARK verifier, a technique called recursive composition. Unfort ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Over-the-Air Computation via Reconfigurable Intelligent Surface

Wei Chen, Yuning Jiang

Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels. However, the performance of AirComp is bott ...

2021

AKSEL: Fast Byzantine SGD

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Sébastien Louis Alexandre Rouault

Modern machine learning architectures distinguish servers and workers. Typically, a d-dimensional model is hosted by a server and trained by n workers, using a distributed stochastic gradient descent (SGD) optimization scheme. At each SGD step, the goal is ...

Schloss Dagstuhl--Leibniz-Zentrum für Informatik2021

Computational tool for stock-constrained design of structures

Corentin Jean Dominique Fivet, Jan Friedrich Georg Brütting, Jonas Warmuth

Designing structures from reused elements is becoming an increasingly important design task for structural engineers as it has potential to significantly reduce adverse environmental impacts of building structures. To allow for a broad application of this ...

2021

Prediction of the reaction forces of spiral-groove gas journal bearings by artificial neural network regression models

Jürg Alexander Schiffmann, Elia Iseli

This paper presents neural network regression models for predicting the nonlinear static and linearized dynamic reaction forces of spiral grooved gas journal bearings. The partial differential equations (PDEs) are sampled, based on a full factorial and ran ...

2021

Minimum energy adaptive structures – All-In-One problem formulation

Gennaro Senatore, Yafeng Wang

This paper presents a new All-In-One (AIO) implementation of an existing formulation to design adaptive structures through Total Energy Optimization (TEO). The method implemented in previous work is a nested optimization process, here named TEO-Nested. Num ...

2020

FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

Rachid Guerraoui, Anne-Marie Kermarrec, Rhicheek Patra, Georgios Damaskinos

Federated Learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no energy or ...

Association for Computing Machinery2020

Dynamics of optical forces and torques in plasmonic systems: a surface integral equation

Olivier Martin, Karim Achouri, Andrei Kiselev

A novel approach is introduced to determine the time evolution of optical forces and torques on arbitrary shape nanostructures by combining Maxwell's stress tensor with the surface integral equation method (SIE). Conventional time averaging of Maxwell’s st ...

SPIEDigitalLibrary2020

Uncertainty propagation based on correlated sampling technique for nuclear data applications

Andreas Pautz, Vincent Pierre Lamirand, Dimitri Rochman, Axel Guy Marie Laureau

A correlated sampling technique has been implemented to estimate the impact of cross section modifications on the neutron transport and in Monte Carlo simulations in one single calculation. This implementation has been coupled to a Total Monte Carlo approa ...

2020

Development and verification of pin-by-pin homogenized simplified transport solver Tortin for PWR core analysis

Andreas Pautz, Petra Mala

Currently, the pin-by-pin homogenized solvers are a very active research field as they can, unlike the nodal codes, directly predict the local power, while requiring significantly less computational resources than the heterogeneous transport codes. This pa ...

2020

Priority coordination of fiber positioners in multi-objects spectrographs

Denis Gillet, Jean-Paul Richard Kneib, Mohamed Bouri, Laleh Makarem

Projects such as "The Dark Energy Spectroscopic Instrument" (DESI) [1] or "The Multi Object Optical and Near-infrared Spectrograph" (MOONS) [5] are developing spectrographs, composed of more than thousand of optical fibers in a confined hexagonal focal pla ...

SPIE-INT SOC OPTICAL ENGINEERING2018

Real-time implementation with FPGA-based DAQ system of a probabilistic disruption predictor from scratch

Olivier Sauter, Martinus Adela Maria Gijs, Jonathan Graves, Ambrogio Fasoli, Stefano Coda, Basil Duval, Henri Weisen, Richard Pitts, Yves Martin, Javier García Hernández, Duccio Testa, Miguel Fernández Ruiz, Nicola Vianello, Robin Humphry-Baker, Sun Hee Kim, Federico Nespoli, Patrick Blanchard, Alessandro Pau, David Pfefferlé, Davide Galassi, Jonathan Marc Philippe Faustin, Cristian Sommariva, Hamish William Patten, Samuel Lanthaler, Jan Horacek, Yann Camenen, Bruno Emanuel Ferreira De Sousa Correia, José Pedro Rebelo Ferreira Marques, Mikhail Maslov, Marco Wischmeier, Dalziel Joseph Wilson, Liang Yao, Daniel Scott Alessi, Arnout Lodewijk M Beckers, Ana Francisca Leal Silva Soares, Jonnathan Cesar Hidalgo Acosta, Antonio José Pereira de Figueiredo, Partha Dutta, Pierre-Thomas Paul Brun, Pedro Camilo de Oliveira e Silva, Alberto Hernando de Castro, Julio Rodriguez, Vlad Trifa, Li Shuai, Rebecca Hill

Real-time (RT) disruption prediction (DP) is essential to trigger mitigation actions that avoid irreversible damage to the devices. This paper deals with disruption mitigation alarms and performs the RT implementation of a probabilistic predictor. The RT i ...

2018

Compressive Spectral Clustering

Pierre Vandergheynst, Rémi Gribonval, Gilles Puy

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

Light Transport Matrix recovery for nearly planar objects

Martin Vetterli, Paolo Prandoni, Loïc Arnaud Baboulaz, Niranjan Thanikachalam

The light transport matrix has become a powerful tool for scene relighting, owing to the versatility of its representational power of various light transport phenomenon. We argue that scenes with an almost planar surface geometry, even with significant amo ...

SPIE2014

FID-guided retrospective motion correction based on autofocusing

Rolf Gruetter, Tobias Kober, Gunnar Krüger, Cristina Granziera, Maryna Volodimirivna Waszak

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

Anatomical Priors to improve Global Tractography

Jean-Philippe Thiran, Alessandro Daducci, Alia Lemkaddem

The main assumption of fiber-tracking algorithms is that fiber trajectories are represented by paths of highest diffusion, which is usually accomplished by following the principal diffusion directions in every voxel. The state-of-the-art approaches known a ...

2014