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Found 13 papers, 3 papers with code
Design of Artificial Interference Signals for Covert Communication Aided by Multiple Friendly Nodes
The optimization aims to design artificial noise signals within the space to facilitate covert communication while minimizing the impact on the performance of legitimate communication.
MCF: Mutual Correction Framework for Semi-Supervised Medical Image Segmentation
Inspired by the plain contrast idea, MCF introduces two different subnets to explore and utilize the discrepancies between subnets to correct cognitive bias of the model.
Edge Graph Neural Networks for Massive MIMO Detection
Massive Multiple-Input Multiple-Out (MIMO) detection is an important problem in modern wireless communication systems.
Multi-Level Contrastive Learning for Cross-Lingual Alignment
Cross-language pre-trained models such as multilingual BERT (mBERT) have achieved significant performance in various cross-lingual downstream NLP tasks.
Secure Transmission for IRS-Assisted MIMO MmWave Systems
In this paper, we investigate the secure beamforming design in an intelligent reflection surface (IRS) assisted millimeter wave (mmWave) system, where the hybrid beamforming (HB) and the passive beamforming (PB) are employed by the transmitter and the IRS, respectively.
Data Informed Residual Reinforcement Learning for High-Dimensional Robotic Tracking Control
The learning inefficiency of reinforcement learning (RL) from scratch hinders its practical application towards continuous robotic tracking control, especially for high-dimensional robots.
Designing Binary Sequence Set with Optimized Correlation Properties via ADMM Approach
In this paper, we design low correlation binary sequences favorable in wireless communication and radar applications.
Indexing Context-Sensitive Reachability
Many context-sensitive data flow analyses can be formulated as a variant of the all-pairs Dyck-CFL reachability problem, which, in general, is of sub-cubic time complexity and quadratic space complexity.
Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework
Theoretical convergence to a (quantized) stationary point of the pdADMM-G algorithm and the pdADMM-G-Q algorithm is provided with a sublinear convergence rate $o(1/k)$, where $k$ is the number of iterations.
Model-Free Incremental Adaptive Dynamic Programming Based Approximate Robust Optimal Regulation
This paper presents a new formulation for model-free robust optimal regulation of continuous-time nonlinear systems.
Efficient QAM Signal Detector for Massive MIMO Systems via PS-ADMM Approach
In this paper, we design an efficient quadrature amplitude modulation (QAM) signal detector for massive multiple-input multiple-output (MIMO) communication systems via the penalty-sharing alternating direction method of multipliers (PS-ADMM).
A Low-Complexity ADMM-based Massive MIMO Detectors via Deep Neural Networks
An alternate direction method of multipliers (ADMM)-based detectors can achieve good performance in both small and large-scale multiple-input multiple-output (MIMO) systems.
Designing Massive MIMO Detector via PS-ADMM approach
Then, the higher modulation signals are decomposed into a sum of multiple binary variables through their inherent structures, by exploiting introduced binary variables as penalty functions, the detection optimization model is equivalent to a nonconvex sharing minimization problem.
