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20102023
most citedNested Polar Codes for Wiretap and Relay Channels

181 citations · 1.2k across the 132 of their papers we have counts for

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Showing 2018Show all

11 papers · 1 filter

cs.IT2018★ 1 cited

The -error Capacity of Symmetric PIR with Byzantine Adversaries

Qiwen Wang, Hua Sun, Mikael Skoglund

The capacity of symmetric private information retrieval with messages, servers (out of which any may collude), and an omniscient Byzantine adversary (who can corrupt an…

math.OC2018★ 1 cited

Privacy-aware Minimum Error Probability Estimation: An Entropy Constrained Approach

Ehsan Nekouei, Henrik Sandberg, Mikael Skoglund +1

This paper studies the design of an optimal privacyaware estimator of a public random variable based on noisy measurements which contain private information. The public random vari…

math.ST2018

Non-Asymptotic Behavior of the Maximum Likelihood Estimate of a Discrete Distribution

Sina Molavipour, Germán Bassi, Mikael Skoglund

In this paper, we study the maximum likelihood estimate of the probability mass function (pmf) of independent and identically distributed (i.i.d.) random variables, in the non-…

cs.IT2018

Delay Performance of the Multiuser MISO Downlink under Imperfect CSI and Finite Length Coding

Sebastian Schiessl, James Gross, Mikael Skoglund +1

We use stochastic network calculus to investigate the delay performance of a multiuser MISO system with zero-forcing beamforming. First, we consider ideal assumptions with long cod…

cs.LG2018

Learning Kolmogorov Models for Binary Random Variables

Hadi Ghauch, Mikael Skoglund, Hossein Shokri-Ghadikolaei +2

We summarize our recent findings, where we proposed a framework for learning a Kolmogorov model, for a collection of binary random variables. More specifically, we derive condition…

cs.LG2018★ 1 cited

A Unified Framework for Training Neural Networks

Hadi Ghauch, Hossein Shokri-Ghadikolaei, Carlo Fischione +1

The lack of mathematical tractability of Deep Neural Networks (DNNs) has hindered progress towards having a unified convergence analysis of training algorithms, in the general sett…