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Olivier Rioul

Publications and source records attributed to Olivier Rioul.

27 records · Page 2Linked to original sources
arXiv2019

Glass+Skin: An Empirical Evaluation of the Added Value of Finger Identification to Basic Single-Touch Interaction on Touch Screens

The usability of small devices such as smartphones or interactive watches is often hampered by the limited size of command vocabularies. This paper is an attempt at better understanding how finger identification may help users invoke commands on touch screens, even without recourse to multi-touch input. We describe how finger identification can increase the size of input vocabularies under the constraint of limited real estate, and we discuss some visual cues to communicate this novel modality to novice users. We report a controlled experiment that evaluated, over a large range of input-vocabulary sizes, the efficiency of single-touch command selections with vs. without finger identification. We analyzed the data not only in terms of traditional time and error metrics, but also in terms of a throughput measure based on Shannon's theory, which we show offers a synthetic and parsimonious account of users' performance. The results show that the larger the input vocabulary needed by the designer, the more promising the identification of individual fingers.

cs.HC↗
arXiv2018

Rényi Entropy Power Inequalities via Normal Transport and Rotation

Following a recent proof of Shannon's entropy power inequality (EPI), a comprehensive framework for deriving various EPIs for the Rényi entropy is presented that uses transport arguments from normal densities and a change of variable by rotation. Simple arguments are given to recover the previously known Rényi EPIs and derive new ones, by unifying a multiplicative form with constant c and a modification with exponent α of previous works. In particular, for log-concave densities, we obtain a simple transportation proof of a sharp varentropy bound.

cs.IT↗
arXiv2017

Optimal Transportation to the Entropy-Power Inequality

We present a simple proof of the entropy-power inequality using an optimal transportation argument which takes the form of a simple change of variables. The same argument yields a reverse inequality involving a conditional differential entropy which has its own interest. It can also be generalized in various ways. The equality case is easily captured by this method and the proof is formally identical in one and several dimensions.

cs.IT↗
arXiv2017

Yet Another Proof of the Entropy Power Inequality

Yet another simple proof of the entropy power inequality is given, which avoids both the integration over a path of Gaussian perturbation and the use of Young's inequality with sharp constant or Rényi entropies. The proof is based on a simple change of variables, is formally identical in one and several dimensions, and easily settles the equality case.

cs.IT↗
arXiv2017

At Every Corner: Determining Corner Points of Two-User Gaussian Interference Channels

The corner points of the capacity region of the two-user Gaussian interference channel under strong or weak interference are determined using the notions of almost Gaussian random vectors, almost lossless addition of random vectors, and almost linearly dependent random vectors. In particular, the "missing" corner point problem is solved in a manner that differs from previous works in that it avoids the use of integration over a continuum of SNR values or of Monge-Kantorovitch transportation problems.

cs.IT↗
arXiv2015

A low-complexity 2D signal space diversity solution for future broadcasting systems

-DVB-T2 was the first industrial standard deploying rotated and cyclic Q delayed (RCQD)modulation to improve performance over fading channels. This enablesimportantgains compared toconventional quadrature amplitude modulations(QAM) under severe channel conditions.However, the corresponding demodulation complexitystill prevents its use forwider applications. This paper proposes several rotation angles for different QAM constellations anda corresponding low-complexity detection method. Results show that the proposed solution simplifies both the transmitter and the receiver with often betterperformancethan the proposed angles in DVB-T2. Compared with the lowest complexity demappers currently used in DVB-T2, the proposed solution achieves an additional reduction bymore than 60%. Index Terms- DVB-T2, Rotated and Cyclic Q Delayed (RCQD) Modulations, Signal Space Diversity (SSD), Fading Channel, Quadrature Amplitude Modulations (QAM), Max-Log, ComputationalComplexity.

cs.IT↗
arXiv2010

Information Theoretic Proofs of Entropy Power Inequalities

While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, up to now Shannon's entropy power inequality (EPI) is an exception: Existing information theoretic proofs of the EPI hinge on representations of differential entropy using either Fisher information or minimum mean-square error (MMSE), which are derived from de Bruijn's identity. In this paper, we first present an unified view of these proofs, showing that they share two essential ingredients: 1) a data processing argument applied to a covariance-preserving linear transformation; 2) an integration over a path of a continuous Gaussian perturbation. Using these ingredients, we develop a new and brief proof of the EPI through a mutual information inequality, which replaces Stam and Blachman's Fisher information inequality (FII) and an inequality for MMSE by Guo, Shamai and Verdú used in earlier proofs. The result has the advantage of being very simple in that it relies only on the basic properties of mutual information. These ideas are then generalized to various extended versions of the EPI: Zamir and Feder's generalized EPI for linear transformations of the random variables, Takano and Johnson's EPI for dependent variables, Liu and Viswanath's covariance-constrained EPI, and Costa's concavity inequality for the entropy power.

cs.IT↗
arXiv2007

A Simple Proof of the Entropy-Power Inequality via Properties of Mutual Information

While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, Shannon's entropy power inequality (EPI) seems to be an exception: available information theoretic proofs of the EPI hinge on integral representations of differential entropy using either Fisher's information (FI) or minimum mean-square error (MMSE). In this paper, we first present a unified view of proofs via FI and MMSE, showing that they are essentially dual versions of the same proof, and then fill the gap by providing a new, simple proof of the EPI, which is solely based on the properties of mutual information and sidesteps both FI or MMSE representations.

cs.IT↗