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Publications associées (257)

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NrOS: Effective Replication and Sharing in an Operating System

Sanidhya Kashyap, Ankit Bhardwaj

Writing a correct operating system kernel is notoriously hard. Kernel code requires manual memory management and type-unsafe code and must efficiently handle complex, asynchronous events. In addition, increasing CPU core counts further complicate kernel de ...

USENIX ASSOC2021

Multikernel Regression with Sparsity Constraint

Michaël Unser, Shayan Aziznejad

In this paper, we provide a Banach-space formulation of supervised learning with generalized total-variation (gTV) regularization. We identify the class of kernel functions that are admissible in this framework. Then, we propose a variation of supervised l ...

2021

MATHICSE Technical Report : Density estimation in RKHS with application to Korobov spaces in high dimensions

Fabio Nobile, Yoshihito Kazashi

A kernel method for estimating a probability density function (pdf) from an i.i.d. sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined by a linear equation. An err ...

MATHICSE2021

Performance of GaN Power Devices for Cryogenic Applications Down to 4.2 K

Elison de Nazareth Matioli, Luca Nela, Palliyage Srilak Nirmana Perera, Catherine Erine

Gallium nitride (GaN) power devices are employed in an increasing number of applications thanks to their excellent performance. Nevertheless, their potential for cryogenic applications, such as space, aviation, and superconducting systems, has not yet been ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Architecture Exploration and Optimization of Heterogeneous Many-Core Compute and Memory Architectures with Architectural Extensions

Yasir Mahmood Qureshi

The expeditious proliferation of Internet connectivity and the growing adoption of digital products have transformed various spheres of our everyday lives. This increased digitization of society has led to the emergence of new applications, which are deplo ...

EPFL2021

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Computer systems designers are building cache hierarchies with higher capacity to capture the ever-increasing working sets of modern workloads. Cache hierarchies with higher capacity improve system performance but shift the performance bottleneck to addres ...

2021

This thesis is centered on questions coming from Machine Learning (ML) and Statistical Field Theory (SFT).In Machine Learning, we consider the subfield of Supervised Learning (SL), and in particular regression tasks where one tries to find a regressor that ...

EPFL2021

What can linearized neural networks actually say about generalization?

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Guillermo Ortiz Jimenez

For certain infinitely-wide neural networks, the neural tangent kernel (NTK) theory fully characterizes generalization, but for the networks used in practice, the empirical NTK only provides a rough first-order approximation. Still, a growing body of work ...

2021

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We propose a deep-learning method for automatically decomposing noisy Monte Carlo renderings into components that kernelpredicting denoisers can denoise more effectively. In our model, a neural decomposition module learns to predict noisy components and co ...

WILEY2021

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In this paper, we present a new flexure-based load cell with adjustable stiffness designed for force sensors with extended force range and respective measuring resolution. This novel monolithic mechanism consists of a T-shaped flexure pivot combined with a ...

euspen2021