Publications associées à Handheld reflectance acquisition of paintings

Publications associées (28)

Extensions of Peer Prediction Incentive Mechanisms

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Stop Wasting my FLOPS: Improving the Efficiency of Deep Learning Models

Angelos Katharopoulos

Deep neural networks have completely revolutionized the field of machine learning by achieving state-of-the-art results on various tasks ranging from computer vision to protein folding. However, their application is hindered by their large computational an ...

EPFL2022

Mechanical intelligence for learning embodied sensor-object relationships

Ahalya Prabhakar

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

Nature Portfolio2022

Room-temperature electrical control of polarization and emission angle in a cavity-integrated 2D pulsed LED

Andras Kis, Dmitrii Unuchek, Fedele Tagarelli, Zhe Sun, Juan Francisco Gonzalez Marin, Cheol Yeon Cheon

Devices based on two-dimensional (2D) semiconductors hold promise for the realization of compact and versatile on-chip interconnects between electrical and optical signals. Although light emitting diodes (LEDs) are fundamental building blocks for integrate ...

Nature Research2022

Defects in III-N LEDs: experimental identification and impact on electro-optical characteristics

Nicolas Grandjean, Jean-François Carlin, Camille Haller

III-N light-emitting-diodes (LEDs) are subject of intense investigations, thanks to their high efficiency and great reliability. The quality of the semiconductor material has a significant impact on the electro-optical performance of LEDs: for this reason, ...

SPIE-INT SOC OPTICAL ENGINEERING2022

Uncertain Sampling with Certain Priors

Golnooshsadat Elhami

Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...

EPFL2021

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Michael Christoph Gastpar, Adriano Pastore

We consider a setup in which confidential i.i.d. samples X1, . . . , Xn from an unknown finite-support distribution p are passed through n copies of a discrete privatization chan- nel (a.k.a. mechanism) producing outputs Y1, . . . , Yn. The channel law gua ...

2021

Distributionally Robust Optimization with Markovian Data

Daniel Kuhn, Tobias Sutter, Mengmeng Li

We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

CPGD: Cadzow Plug-and-Play Gradient Descent for Generalised FRI

Martin Vetterli, Paul Hurley, Matthieu Martin Jean-André Simeoni, Adrien Georges Jean Besson

Finite rate of innovation (FRI) is a powerful reconstruction framework enabling the recovery of sparse Dirac streams from uniform low-pass filtered samples. An extension of this framework, called generalised FRI (genFRI), has been recently proposed for han ...

2020

Multi-User Precoder Designs for RGB Visible Light Communication Systems

Roser Vinals Terres

In this paper, we design linear precoders for the downlink of a visible light communication (VLC) system that simultaneously serves multiple users. Instead of using phosphor-coated white light-emitting diodes (PWLEDs), we focus on Red-Green-Blue light-emit ...

2020

Multivariate extremes over a random number of observations

Simone Padoan, Stefano Rizzelli

The classical multivariate extreme-value theory concerns the modeling of extremes in a multivariate random sample, suggesting the use of max-stable distributions. In this work, the classical theory is extended to the case where aggregated data, such as max ...

WILEY2021

Variance-Reduced Stochastic Learning Under Random Reshuffling

Ali H. Sayed, Kun Yuan, Bicheng Ying

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizer. The existing convergence results assume uniform d ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Multithermal-Multibaric Molecular Simulations from a Variational Principle

Pablo Miguel Piaggi

We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev. Lett. 113, 0906 ...

2019

Particle number control for direct simulation Monte-Carlo methodology using kernel estimates

Mohammadhossein Gorji

The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...

2019

Elucidating the role of the InGaN UL in the efficiency of InGaN based light-emitting diodes

Camille Haller

Blue III-nitride light-emitting diodes (LEDs) are widely used nowadays in solid-state lighting, as white light can be produced by combining yellow phosphors and blue LEDs. This technology has the advantage to have a higher luminous efficiency than incandes ...

EPFL2019

InAlN underlaver for near ultraviolet InGaN based light emitting diodes

Nicolas Grandjean, Jean-François Carlin, Camille Haller

We report on InAlN underlayer (UL) to improve the efficiency of near ultraviolet (NUV) light emitting diodes (LEDs). While InGaN UL is commonly used in high-efficiency blue LEDs it may absorb light for shorter wavelengths. InAlN lattice-matched to GaN exhi ...

2019

Electroluminescence of Single InGaN/GaN Micropyramids

Hua Zhang, Gwénolé Jean Jacopin

The results of the fabrication of technological regimes of formation and the study of the optical properties of light emitting diodes (LED) micropyramids based on InGaN/GaN are presented. The structures were formed by the method of Metalorganic vapour-phas ...

PLEIADES PUBLISHING INC2019

Sampling at unknown locations: Uniqueness and reconstruction under constraints

Martin Vetterli, Adam James Scholefield, Benjamin Bejar Haro, Golnooshsadat Elhami, Michalina Wanda Pacholska

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. Without further constraints, the problem is of ...

2018

Unified Theory for Recovery of Sparse Signals in a General Transform Domain

Kyong Hwan Jin

Compressed sensing is provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that the practical algorithms provide robust recovery from noisy linear measurements acquired at a near optimal sampling rate. In many real-world a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Learning without Smoothness and Strong Convexity

Yen-Huan Li

Recent advances in statistical learning and convex optimization have inspired many successful practices. Standard theories assume smoothness---bounded gradient, Hessian, etc.--- and strong convexity of the loss function. Unfortunately, such conditions may ...

EPFL2018