Handheld reflectance acquisition of paintings

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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 ...

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 ...

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 ...

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 ...

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, ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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, ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Handheld reflectance acquisition of paintings

Chattez avec Graph Search

Extensions of Peer Prediction Incentive Mechanisms

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

Mechanical intelligence for learning embodied sensor-object relationships

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

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

Uncertain Sampling with Certain Priors

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Distributionally Robust Optimization with Markovian Data

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

Multi-User Precoder Designs for RGB Visible Light Communication Systems

Multivariate extremes over a random number of observations

Variance-Reduced Stochastic Learning Under Random Reshuffling

Multithermal-Multibaric Molecular Simulations from a Variational Principle

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

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

InAlN underlaver for near ultraviolet InGaN based light emitting diodes

Electroluminescence of Single InGaN/GaN Micropyramids

Sampling at unknown locations: Uniqueness and reconstruction under constraints

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

Learning without Smoothness and Strong Convexity