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We introduce a comprehensive approach to enhance the security, privacy, and sensing capabilities of integrated sensing and communications (ISAC) systems by leveraging random frequency agility (RFA) and random pulse repetition interval (PRI)…

We address the problem of simultaneously learning and control in an online receding horizon control setting. We consider the control of an unknown linear dynamical system with general cost functions and affine constraints on the control…

Optimization and Control · Mathematics 2022-11-02 Deepan Muthirayan , Jianjun Yuan , Pramod P. Khargonekar

We propose the first model-free algorithm that achieves low regret performance for decentralized learning in two-player zero-sum tabular stochastic games with infinite-horizon average-reward objective. In decentralized learning, the…

Machine Learning · Computer Science 2023-01-16 Romain Cravic , Nicolas Gast , Bruno Gaujal

Regret minimization has played a key role in online learning, equilibrium computation in games, and reinforcement learning (RL). In this paper, we describe a general model-free RL method for no-regret learning based on repeated…

In this paper, we investigate a distributed multi-input multi-output and orthogonal frequency division multiplexing (MIMO-OFDM) dual-function radar-communication (DFRC) system, which enables simultaneous communication and sensing in…

Signal Processing · Electrical Eng. & Systems 2025-03-17 Chen Zhong , Xufeng Zhou , Lan Tang , Mengting Lou

The long-run behavior of multi-agent learning - and, in particular, no-regret learning - is relatively well-understood in potential games, where players have aligned interests. By contrast, in harmonic games - the strategic counterpart of…

Computer Science and Game Theory · Computer Science 2024-12-31 Davide Legacci , Panayotis Mertikopoulos , Christos H. Papadimitriou , Georgios Piliouras , Bary S. R. Pradelski

This paper considers the distributed online convex-concave optimization with constraint sets over a multiagent network, in which each agent autonomously generates a series of decision pairs through a designable mechanism to cooperatively…

Optimization and Control · Mathematics 2025-08-14 Wentao Zhang , Baoyong Zhang , Deming Yuan , Shengyuan Xu , Vincent K. N. Lau

Deep neural networks are incredibly vulnerable to crafted, human-imperceptible adversarial perturbations. Although adversarial training (AT) has proven to be an effective defense approach, we find that the AT-trained models heavily rely on…

Computer Vision and Pattern Recognition · Computer Science 2022-12-27 Binxiao Huang , Chaofan Tao , Rui Lin , Ngai Wong

Radar is of vital importance in many fields, such as autonomous driving, safety and surveillance applications. However, it suffers from stringent constraints on its design parametrization leading to multiple trade-offs. For example, the…

Computer Vision and Pattern Recognition · Computer Science 2019-11-26 Karim Armanious , Sherif Abdulatif , Fady Aziz , Urs Schneider , Bin Yang

Frequency-hopping (FH) MIMO radar-based dual-function radar communication (FH-MIMO DFRC) enables communication symbol rate to exceed radar pulse repetition frequency, which requires accurate estimations of timing offset and channel…

Signal Processing · Electrical Eng. & Systems 2021-05-31 Kai Wu , J. Andrew Zhang , Xiaojing Huang , Y. Jay Guo , Robert W. Heath

Existing online learning algorithms for adversarial Markov Decision Processes achieve ${O}(\sqrt{T})$ regret after $T$ rounds of interactions even if the loss functions are chosen arbitrarily by an adversary, with the caveat that the…

Machine Learning · Computer Science 2023-10-27 Tiancheng Jin , Junyan Liu , Chloé Rouyer , William Chang , Chen-Yu Wei , Haipeng Luo

Integrated sensing and communication is a key feature in next-generation wireless networks, enabling joint data transmission and environmental radar sensing on shared spectrum. In multi-user scenarios, simultaneous transmissions cause…

Signal Processing · Electrical Eng. & Systems 2026-01-30 Laurits Randers , Martin Voigt Vejling , Petar Popovski

In harmonic radar (HR), the radio frequency transmitter illuminates a nonlinear target (the tag), causing the return signal to consist of harmonics at multiples of the transmitted carrier frequency. Of them, the second harmonic is usually…

Signal Processing · Electrical Eng. & Systems 2022-05-11 Anastasia Lavrenko , James K. Cavers , Graeme K. Woodward

This paper studies distributionally robust regret-optimal (DRRO) control with purified output feedback for linear systems subject to additive disturbances and measurement noise. These uncertainties (including the initial system state) are…

Optimization and Control · Mathematics 2025-11-21 Shuhao Yan , Carsten W. Scherer

Regret minimization is treated as the golden rule in the traditional study of online learning. However, regret minimization algorithms tend to converge to the static optimum, thus being suboptimal for changing environments. To address this…

Machine Learning · Computer Science 2020-02-07 Lijun Zhang , Shiyin Lu , Tianbao Yang

We consider an online channel scheduling problem for a single transmitter-receiver pair equipped with $N$ arbitrarily varying wireless channels. The transmission rates of the channels might be non-stationary and could be controlled by an…

Information Theory · Computer Science 2025-01-24 G Krishnakumar , Abhishek Sinha

Frequency-modulated continuous-wave (FMCW) scanning radar has emerged as an alternative to spinning LiDAR for state estimation on mobile robots. Radar's longer wavelength is less affected by small particulates, providing operational…

Robotics · Computer Science 2024-09-17 Xinyuan Qiao , Alexander Krawciw , Sven Lilge , Timothy D. Barfoot

We consider control in linear time-varying dynamical systems from the perspective of regret minimization. Unlike most prior work in this area, we focus on the problem of designing an online controller which minimizes regret against the best…

Machine Learning · Computer Science 2021-02-03 Gautam Goel , Babak Hassibi

A multi-user multi-armed bandit (MAB) framework is used to develop algorithms for uncoordinated spectrum access. The number of users is assumed to be unknown to each user. A stochastic setting is first considered, where the rewards on a…

Machine Learning · Computer Science 2019-01-31 Meghana Bande , Venugopal V. Veeravalli

Dual-function radar-communication (DFRC) based on frequency hopping (FH) MIMO radar (FH-MIMO DFRC) achieves symbol rate much higher than radar pulse repetition frequency. Such DFRC, however, is prone to eavesdropping due to the spatially…

Signal Processing · Electrical Eng. & Systems 2020-09-30 Kai Wu , J. Andrew Zhang , Xiaojing Huang , Y. Jay Guo
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