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20042020
most citedDirect Localization for Massive MIMO

391 citations

Showing 2015Show all

22 papers · 1 filter

cs.LG2015101 cited

Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM

Léa Laporte, Rémi Flamary, Stephane Canu +2

Feature selection in learning to rank has recently emerged as a crucial issue. Whereas several preprocessing approaches have been proposed, only a few works have been focused on in…

math.RT20151 cited

Geometric side of a local relative trace formula

Patrick Delorme, Pascale Harinck, Sofiane Souaifi

Following a scheme suggested by B. Feigon, we investigate a local relative trace formula in the situation of a reductive -adic group relative to a symmetric subgroup $H= \u…

q-bio.NC201515 cited

Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification

J Spinnato, M-C Roubaud, B Burle +1

Objective. The main goal of this work is to develop a model for multi-sensor signals such as MEG or EEG signals, that accounts for the inter-trial variability, suitable for corresp…

math.PR201551 cited

Rigidity of Determinantal Point Processes with the Airy, the Bessel and the Gamma Kernel

Alexander I. Bufetov

A point process is said to be rigid if for any bounded domain in the phase space, the number of particles in the domain is almost surely determined by the restriction of the config…

math.AG20156 cited

On the distribution of the trace in the unitary symplectic group and the distribution of Frobenius

Gilles Lachaud

The purpose of this article is to study the distribution of the trace on the unitary symplectic group. We recall its relevance to equidistribution results for the eigenvalues of th…

math.AP20157 cited

Partial analyticity and nodal sets for nonlinear elliptic systems

Herbert Koch, Nikolai Nadirashvili

We study partial analyticity of solutions to elliptic systems and analyticity of level sets of solutions to nonlinear elliptic systems. We consider several applications, including…