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pro vyhledávání: '"P. Skoglund"'
Akademický článek
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A fundamental problem in decentralized networked systems is to coordinate actions of different agents so that they reach a state of agreement. In such applications, it is additionally desirable that the actions at various nodes may not be anticipated
Externí odkaz:
http://arxiv.org/abs/2411.14123
In this paper, we investigate the performance of an integrated sensing and communication (ISAC) system within a cell-free massive multiple-input multiple-output (MIMO) system. Each access point (AP) operates in the millimeter-wave (mmWave) frequency
Externí odkaz:
http://arxiv.org/abs/2411.08759
Autor:
Bongole, Raghav, Gouverneur, Amaury, Rodríguez-Gálvez, Borja, Oechtering, Tobias J., Skoglund, Mikael
We study agents acting in an unknown environment where the agent's goal is to find a robust policy. We consider robust policies as policies that achieve high cumulative rewards for all possible environments. To this end, we consider agents minimizing
Externí odkaz:
http://arxiv.org/abs/2410.16013
In this paper, we present SCOREQ, a novel approach for speech quality prediction. SCOREQ is a triplet loss function for contrastive regression that addresses the domain generalisation shortcoming exhibited by state of the art no-reference speech qual
Externí odkaz:
http://arxiv.org/abs/2410.06675
Autor:
Zamani, Amirreza, Skoglund, Mikael
This paper provides an overview of a problem in information-theoretic privacy mechanism design, addressing two scenarios in which private data is either observable or hidden. In each scenario, different privacy measures are used, including bounded mu
Externí odkaz:
http://arxiv.org/abs/2410.05033
Integrated sensing and communications (ISAC) is a promising component of 6G networks, fusing communication and radar technologies to facilitate new services. Additionally, the use of extremely large-scale antenna arrays (ELLA) at the ISAC common rece
Externí odkaz:
http://arxiv.org/abs/2410.04930
Autor:
Zamani, Amirreza, Skoglund, Mikael
A statistical cache-aided compression problem with a privacy constraint is studied, where a server has access to a database of $N$ files, $(Y_1,...,Y_N)$, each of size $F$ bits and is linked through a shared channel to $K$ users, where each has acces
Externí odkaz:
http://arxiv.org/abs/2409.20133
In this article, we study the fundamental limits in the design of fair and/or private representations achieving perfect demographic parity and/or perfect privacy through the lens of information theory. More precisely, given some useful data $X$ that
Externí odkaz:
http://arxiv.org/abs/2408.13168
We investigate the in-distribution generalization of machine learning algorithms. We depart from traditional complexity-based approaches by analyzing information-theoretic bounds that quantify the dependence between a learning algorithm and the train
Externí odkaz:
http://arxiv.org/abs/2408.13275