270 citations · 878 across the 64 of their papers we have counts for
9 papers · 1 filter
Reconfigurable Intelligent Surface-induced Randomness for mmWave Key Generation
Shubo Yang, Han Han, Yihong Liu +3
Secret key generation in physical layer security exploits the unpredictable random nature of wireless channels. The millimeter-wave (mmWave) channels have limited multipath and cha…
Blockchain Systems, Technologies and Applications: A Methodology Perspective
Bin Cao, Zixin Wang, Long Zhang +3
In the past decade, blockchain has shown a promising vision greatly to build the trust without any powerful third party in a secure, decentralized and salable manner. However, due…
Training a First-Order Theorem Prover from Synthetic Data
Vlad Firoiu, Eser Aygun, Ankit Anand +6
A major challenge in applying machine learning to automated theorem proving is the scarcity of training data, which is a key ingredient in training successful deep learning models.…
Pluggable Weakly-Supervised Cross-View Learning for Accurate Vehicle Re-Identification
Lu Yang, Hongbang Liu, Jinghao Zhou +4
Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under…
Dual MINE-based Neural Secure Communications under Gaussian Wiretap Channel
Jingjing Li, Zhuo Sun, Lei Zhang +1
Recently, some researches are devoted to the topic of end-to-end learning a physical layer secure communication system based on autoencoder under Gaussian wiretap channel. However,…
Resource Allocation for Mixed Numerology NOMA
Stephen McWade, Mark F. Flanagan, Juquan Mao +2
6G wireless networks will require the flexibility to accommodate an extremely diverse set of service types. This necessitates the use of mixed numerologies to accommodate different…
Reinforcement Learning for Flexibility Design Problems
Yehua Wei, Lei Zhang, Ruiyi Zhang +3
Flexibility design problems are a class of problems that appear in strategic decision-making across industries, where the objective is to design a (, manufacturing) network t…
Self-supervised Pre-training with Hard Examples Improves Visual Representations
Chunyuan Li, Xiujun Li, Lei Zhang +3
Self-supervised pre-training (SSP) employs random image transformations to generate training data for visual representation learning. In this paper, we first present a modeling fra…
Unsupervised Domain Adaptation of Black-Box Source Models
Haojian Zhang, Yabin Zhang, Kui Jia +1
Unsupervised domain adaptation (UDA) aims to learn models for a target domain of unlabeled data by transferring knowledge from a labeled source domain. In the traditional UDA setti…