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Bayesian hierarchical models can provide efficient algorithms for finding sparse solutions to ill-posed inverse problems. The models typically comprise a conditionally Gaussian prior model for the unknown which is augmented by a generalized…

Numerical Analysis · Mathematics 2025-01-09 Jonathan Lindbloom , Jan Glaubitz , Anne Gelb

We present new algorithms for inverse reinforcement learning (IRL, or inverse optimal control) in convex optimization settings. We argue that finite-space IRL can be posed as a convex quadratic program under a Bayesian inference framework…

Machine Learning · Computer Science 2013-01-22 Qifeng Qiao , Peter A. Beling

Detecting anomalies in multivariate time-series data is essential in many real-world applications. Recently, various deep learning-based approaches have shown considerable improvements in time-series anomaly detection. However, existing…

Machine Learning · Computer Science 2022-01-31 Kyeong-Joong Jeong , Yong-Min Shin

Reconfigurable intelligent surface (RIS) is a two-dimensional periodic structure integrated with a large number of reflective elements, which can manipulate electromagnetic waves in a digital way, offering great potentials for wireless…

Machine Learning · Computer Science 2025-01-22 Zhen Zhang , Jun Hui Qiu , Jun Wei Zhang , Hui Dong Li , Dong Tang , Qiang Cheng , Wei Lin

In this paper, the problem of robust reconfigurable intelligent surface (RIS) system design under changes in data distributions is investigated. Using the notion of invariant risk minimization (IRM), an invariant causal representation…

Machine Learning · Computer Science 2021-05-06 Sumudu Samarakoon , Jihong Park , Mehdi Bennis

We present a data-assisted iterative regularization method for solving ill-posed inverse problems. The proposed approach, termed \texttt{IRMGL+\(\Psi\)}, integrates classical iterative techniques with a data-driven regularization term…

Numerical Analysis · Mathematics 2025-10-28 Harshit Bajpai , Gaurav Mittal , Ankik Kumar Giri

This note presents a unified analysis of the identification of dynamical systems with low-rank constraints under high-dimensional scaling. This identification problem for dynamic systems are challenging due to the intrinsic dependency of…

Statistics Theory · Mathematics 2019-12-23 Junlin Li

The recovery of sparse data is at the core of many applications in machine learning and signal processing. While such problems can be tackled using $\ell_1$-regularization as in the LASSO estimator and in the Basis Pursuit approach,…

Optimization and Control · Mathematics 2021-11-15 Christian Kümmerle , Claudio Mayrink Verdun , Dominik Stöger

Intelligent reflecting surface (IRS) is a promising technology for enhancing wireless communication systems. It adaptively configures massive passive reflecting elements to control wireless channel in a desirable way. Due to hardware…

Systems and Control · Electrical Eng. & Systems 2021-11-04 Rui Sun , Weidong Wang , Li Chen , Guo Wei , Wenyi Zhang

Reconfigurable Intelligent Surfaces (RIS) are considered a key enabler to achieve the vision of Smart Radio Environments, where the propagation environment can be programmed and controlled to enhance the efficiency of wireless systems.…

Networking and Internet Architecture · Computer Science 2023-01-24 Charbel Bou Chaaya , Mohamad Assaad , Tijani Chahed

Direction-of-Arrival (DoA) estimation assisted with an Intelligent Reflecting Surface (IRS) is crucial for various wireless applications, especially in challenging Non-Line-of-Sight (NLoS) environments. This paper presents a novel neural…

Signal Processing · Electrical Eng. & Systems 2025-05-23 Yasin Azhdari , Mahmoud Farhang

Hypothesis testing based on surrogate data has emerged as a popular way to test the null hypothesis that a signal is a realization of a linear stochastic process. Typically, this is done by generating surrogates which are made to conform to…

Chaotic Dynamics · Physics 2010-08-12 Diego Guarin , Alvaro Orozco , Edilson Delgado

IRGAN is an information retrieval (IR) modeling approach that uses a theoretical minimax game between a generative and a discriminative model to iteratively optimize both of them, hence unifying the generative and discriminative approaches.…

Information Retrieval · Computer Science 2019-10-02 Moksh Jain , Sowmya Kamath S

There has been a growing interest in using non-parametric regression methods like Gaussian Process (GP) regression for system identification. GP regression does traditionally have three important downsides: (1) it is computationally…

Machine Learning · Statistics 2017-08-17 Hildo Bijl , Thomas B. Schön , Jan-Willem van Wingerden , Michel Verhaegen

Autonomous driving and intelligent transportation applications have dramatically increased the demand for high-accuracy and low-latency localization services. While cellular networks are potentially capable of target detection and…

Information Theory · Computer Science 2024-01-08 Kaitao Meng , Qingqing Wu , Wen Chen , Deshi Li

The Bayesian statistical framework provides a systematic approach to enhance the regularization model by incorporating prior information about the desired solution. For the Bayesian linear inverse problems with Gaussian noise and Gaussian…

Numerical Analysis · Mathematics 2024-05-21 Haibo Li

In this contribution, we derive ILEG, an iterative algorithm to find risk sensitive solutions to nonlinear, stochastic optimal control problems. The algorithm is based on a linear quadratic approximation of an exponential risk sensitive…

Systems and Control · Computer Science 2015-12-23 Farbod Farshidian , Jonas Buchli

Reconstructing the causal network in a complex dynamical system plays a crucial role in many applications, from sub-cellular biology to economic systems. Here we focus on inferring gene regulation networks (GRNs) from perturbation or gene…

Quantitative Methods · Quantitative Biology 2016-12-21 Hoi-To Wai , Anna Scaglione , Uzi Harush , Baruch Barzel , Amir Leshem

This paper proposes an intelligent reflecting surface (IRS) assisted integrated sensing and communication (ISAC) system operating at the millimeter-wave (mmWave) band. Specifically, the ISAC system combines communication and radar…

Signal Processing · Electrical Eng. & Systems 2024-04-10 Zhengyu Zhu , Zheng Li , Zheng Chu , Gangcan Sun , Wanming Hao , Pei Xiao , Inkyu Lee

We consider optimal experimental design for parameter estimation in dynamical systems governed by controlled ordinary differential equations. In such problems, Fisher-based criteria are attractive because they lead to time-additive…

Optimization and Control · Mathematics 2026-04-08 Luc de Montella , Sebastian Sager
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