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Continuous aperture array (CAPA) is considered a promising technology for 6G networks, offering the potential to fully exploit spatial DoFs and achieve the theoretical limits of channel capacity. This paper investigates the performance gain…

Signal Processing · Electrical Eng. & Systems 2025-02-27 Mingjun Sun , Chongjun Ouyang , Zhaolin Wang , Shaochuan Wu , Yuanwei Liu

Selecting the optimal set of countermeasures is a challenging task that involves various considerations and tradeoffs such as prioritizing the risks to mitigate and costs. The vast majority of studies for selecting a countermeasure…

Cryptography and Security · Computer Science 2019-06-27 Orly Stan , Ron Bitton , Michal Ezrets , Moran Dadon , Masaki Inokuchi , Yoshinobu Ohta , Tomohiko Yagyu , Yuval Elovici , Asaf Shabtai

It is shown how correlations in the generalized feedback shift-register (GFSR) random-number generator are greatly diminished when the number of feedback taps is increased from two to four (or more) and the tap offsets are lengthened.…

Disordered Systems and Neural Networks · Physics 2009-10-30 Robert M. Ziff

Large language models (LLMs) can memorize and reproduce training sequences verbatim -- a tendency that undermines both generalization and privacy. Existing mitigation methods apply interventions uniformly, degrading performance on the…

Machine Learning · Computer Science 2026-02-10 Xuanqi Zhang , Haoyang Shang , Xiaoxiao Li

This paper proposes a novel algorithm to optimally size and place storage in low voltage (LV) networks based on a linearized multiperiod optimal power flow method which we call forward backward sweep optimal power flow (FBS-OPF). We show…

Systems and Control · Computer Science 2019-03-19 Philipp Fortenbacher , Martin Zellner , Göran Andersson

The Gaussian process state-space model (GPSSM) has garnered considerable attention over the past decade. However, the standard GP with a preliminary kernel, such as the squared exponential kernel or Mat\'{e}rn kernel, that is commonly used…

Machine Learning · Computer Science 2023-04-07 Zhid Lin , Feng Yin , Juan Maroñas

Generative flow networks (GFlowNets) are amortized variational inference algorithms that treat sampling from a distribution over compositional objects as a sequential decision-making problem with a learnable action policy. Unlike other…

In this paper, we propose a general robust subband adaptive filtering (GR-SAF) scheme against impulsive noise by minimizing the mean square deviation under the random-walk model with individual weight uncertainty. Specifically, by choosing…

Signal Processing · Electrical Eng. & Systems 2022-08-22 Yi Yu , Hongsen He , Rodrigo C. de Lamare , Badong Chen

The problem of estimating a sparse channel, i.e. a channel with a few non-zero taps, appears in various areas of communications. Recently, we have developed an algorithm based on iterative alternating minimization which iteratively detects…

Information Theory · Computer Science 2013-08-27 Rad Niazadeh , Masoud Babaie-Zadeh , Christian Jutten

Due to its sound theoretical basis and practical efficiency, masking has become the most prominent countermeasure to protect cryptographic implementations against physical side-channel attacks (SCAs). The core idea of masking is to randomly…

Cryptography and Security · Computer Science 2021-07-22 Thilo Krachenfels , Fatemeh Ganji , Amir Moradi , Shahin Tajik , Jean-Pierre Seifert

Graph neural networks (GNNs) are emerging as a powerful technique for modeling graph structures. Due to the sparsity of real-world graph data, GNN performance is limited by extensive sparse matrix multiplication (SpMM) operations involved…

Machine Learning · Computer Science 2021-11-02 Shenghao Qiu , You Liang , Zheng Wang

We propose a novel sparse spectrum approximation of Gaussian process (GP) tailored for Bayesian optimization. Whilst the current sparse spectrum methods provide desired approximations for regression problems, it is observed that this…

Machine Learning · Computer Science 2020-06-09 Ang Yang , Cheng Li , Santu Rana , Sunil Gupta , Svetha Venkatesh

Hash table search strategies have remained a pivotal area of inquiry in computer science over the past several decades. A prevailing viewpoint asserts that random probing stands as the optimal method for open-addressing hash tables.…

Data Structures and Algorithms · Computer Science 2025-03-24 Qiantong Wang

This paper proposes a generic approach for providing enhanced security to communication systems which encode their data for reliability before encrypting it through a stream cipher for security. We call this counter-intuitive technique the…

Cryptography and Security · Computer Science 2010-08-06 Frederique Oggier , Miodrag J. Mihaljevic

Federated Learning (FL) enables geographically distributed clients to collaboratively train machine learning models by sharing only their local models, ensuring data privacy. However, FL is vulnerable to untargeted attacks that aim to…

Machine Learning · Computer Science 2025-05-21 Di Wu , Qian Li , Heng Yang , Yong Han

Optimal signaling for secrecy rate maximization in Gaussian MIMO wiretap channels is considered. While this channel has attracted a significant attention recently and a number of results have been obtained, including the proof of the…

Information Theory · Computer Science 2016-11-18 Sergey Loyka , Charalambos D. Charalambous

In this paper, an efficient fragile blind quad watermarking scheme for image tamper detection and recovery based on lifting wavelet transform and genetic algorithm is proposed. TRLG generates four compact digests with super quality based on…

Cryptography and Security · Computer Science 2018-03-09 Behrouz Bolourian Haghighi , Amir Hossein Taherinia , Amir Hossein Mohajerzadeh

This paper investigates physical layer security for a large-scale WSN with random multiple access, where each fusion center in the network randomly schedules a number of sensors to upload their sensed data subject to the overhearing of…

Information Theory · Computer Science 2022-04-14 Tong-Xing Zheng , Xin Chen , Chao Wang , Kai-Kit Wong , Jinhong Yuan

We introduce a new online algorithm for expected log-likelihood maximization in situations where the objective function is multi-modal and/or has saddle points, that we term G-PFSO. The key element underpinning G-PFSO is a probability…

Machine Learning · Statistics 2022-07-07 Mathieu Gerber , Randal Douc

In this paper, we investigate combining blocking and collapsing -- two widely used strategies for improving the accuracy of Gibbs sampling -- in the context of probabilistic graphical models (PGMs). We show that combining them is not…

Artificial Intelligence · Computer Science 2013-09-27 Deepak Venugopal , Vibhav Gogate