91 citations · 95 across the 13 of their papers we have counts for
15 papers
Variational Quantum Integrated Sensing and Communication
Ivana Nikoloska, Osvaldo Simeone
The integration of sensing and communication functionalities within a common system is one of the main innovation drivers for next-generation networks. In this paper, we introduce…
Adaptive Bayesian Single-Shot Quantum Sensing
Ivana Nikoloska, Ruud Van Sloun, Osvaldo Simeone
Quantum sensing harnesses the unique properties of quantum systems to enable precision measurements of physical quantities such as time, magnetic and electric fields, acceleration,…
Dynamic Estimation Loss Control in Variational Quantum Sensing via Online Conformal Inference
Ivana Nikoloska, Hamdi Joudeh, Ruud van Sloun +1
Quantum sensing exploits non-classical effects to overcome limitations of classical sensors, with applications ranging from gravitational-wave detection to nanoscale imaging. Howev…
Time-Warping Invariant Quantum Recurrent Neural Networks via Quantum-Classical Adaptive Gating
Ivana Nikoloska, Osvaldo Simeone, Leonardo Banchi +1
Adaptive gating plays a key role in temporal data processing via classical recurrent neural networks (RNN), as it facilitates retention of past information necessary to predict the…
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems
Lisha Chen, Sharu Theresa Jose, Ivana Nikoloska +3
Deep learning has achieved remarkable success in many machine learning tasks such as image classification, speech recognition, and game playing. However, these breakthroughs are of…
Quantum-Aided Meta-Learning for Bayesian Binary Neural Networks via Born Machines
Ivana Nikoloska, Osvaldo Simeone
Near-term noisy intermediate-scale quantum circuits can efficiently implement implicit probabilistic models in discrete spaces, supporting distributions that are practically infeas…
Training Hybrid Classical-Quantum Classifiers via Stochastic Variational Optimization
Ivana Nikoloska, Osvaldo Simeone
Quantum machine learning has emerged as a potential practical application of near-term quantum devices. In this work, we study a two-layer hybrid classical-quantum classifier in wh…
Bayesian Active Meta-Learning for Black-Box Optimization
Ivana Nikoloska, Osvaldo Simeone
Data-efficient learning algorithms are essential in many practical applications for which data collection is expensive, e.g., for the optimal deployment of wireless systems in unkn…
Modular Meta-Learning for Power Control via Random Edge Graph Neural Networks
Ivana Nikoloska, Osvaldo Simeone
In this paper, we consider the problem of power control for a wireless network with an arbitrarily time-varying topology, including the possible addition or removal of nodes. A dat…
Fast Power Control Adaptation via Meta-Learning for Random Edge Graph Neural Networks
Ivana Nikoloska, Osvaldo Simeone
Power control in decentralized wireless networks poses a complex stochastic optimization problem when formulated as the maximization of the average sum rate for arbitrary interfere…
Deep Reinforcement Learning-Aided Random Access
Ivana Nikoloska, Nikola Zlatanov
We consider a system model comprised of an access point (AP) and K Internet of Things (IoT) nodes that sporadically become active in order to send data to the AP. The AP is assumed…
Inference over Wireless IoT Links with Importance-Filtered Updates
Ivana Nikoloska, Josefine Holm, Anders Kalør +2
We consider a communication cell comprised of Internet-of-Things (IoT) nodes transmitting to a common Access Point (AP). The nodes in the cell are assumed to generate data samples…
On the Secrecy Capacity of a Full-Duplex Wirelessly Powered Communication System
Ivana Nikoloska, Nikola Zlatanov, Zoran Hadzi-Velkov +1
In this paper, we investigate the secrecy capacity of a point-to-point, full-duplex (FD) wirelesly powered communication system in the presence of a passive eavesdropper (EVE). The…
Capacity of a Full-Duplex Wirelessly Powered Communication System with Self-Interference and Processing Cost
Ivana Nikoloska, Nikola Zlatanov, Zoran Hadzi-Velkov
In this paper, we investigate the capacity of a point-to-point, full-duplex (FD), wirelessly powered communication system impaired by self-interference. This system is comprised of…
Wireless Networks with Energy Harvesting and Power Transfer: Joint Power and Time Allocation
Zoran Hadzi-Velkov, Ivana Nikoloska, George K. Karagiannidis +1
In this paper, we consider wireless powered communication networks which could operate perpetually, as the base station (BS) broadcasts energy to the multiple energy harvesting (EH…