210 citations · 1.8k across the 103 of their papers we have counts for
35 papers · 1 filter
Wireless Channel Delay Spread Performance Evaluation of a Building Layout
Yixin Huang, Jiliang Zhang, Jie Zhang
Evaluating a building's wireless performance during the building design process is a new paradigm for wireless communications and building design. This paper proposes the earliest…
Backdoor Attacks on Multiagent Collaborative Systems
Shuo Chen, Yue Qiu, Jie Zhang
Backdoor attacks on reinforcement learning implant a backdoor in a victim agent's policy. Once the victim observes the trigger signal, it will switch to the abnormal mode and fail…
Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning
Xueyang Tang, Song Guo, Jie Zhang
Recently, data heterogeneity among the training datasets on the local clients (a.k.a., Non-IID data) has attracted intense interest in Federated Learning (FL), and many personalize…
FedTune: A Deep Dive into Efficient Federated Fine-Tuning with Pre-trained Transformers
Jinyu Chen, Wenchao Xu, Song Guo +3
Federated Learning (FL) is an emerging paradigm that enables distributed users to collaboratively and iteratively train machine learning models without sharing their private data.…
Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning
Yi Liu, Song Guo, Jie Zhang +3
To eliminate the requirement of fully-labeled data for supervised model training in traditional Federated Learning (FL), extensive attention has been paid to the application of Sel…
Reinforcement Learning Enhanced Weighted Sampling for Accurate Subgraph Counting on Fully Dynamic Graph Streams
Kaixin Wang, Cheng Long, Da Yan +2
As the popularity of graph data increases, there is a growing need to count the occurrences of subgraph patterns of interest, for a variety of applications. Many graphs are massive…
VATLM: Visual-Audio-Text Pre-Training with Unified Masked Prediction for Speech Representation Learning
Qiushi Zhu, Long Zhou, Ziqiang Zhang +7
Although speech is a simple and effective way for humans to communicate with the outside world, a more realistic speech interaction contains multimodal information, e.g., vision, t…
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
Cong Zhang, Zhiguang Cao, Wen Song +2
Recent studies in using deep reinforcement learning (DRL) to solve Job-shop scheduling problems (JSSP) focus on construction heuristics. However, their performance is still far fro…
From RDMA to RDCA: Toward High-Speed Last Mile of Data Center Networks Using Remote Direct Cache Access
Qiang Li, Qiao Xiang, Derui Liu +21
In this paper, we conduct systematic measurement studies to show that the high memory bandwidth consumption of modern distributed applications can lead to a significant drop of net…
A Comparative Study on Multichannel Speaker-Attributed Automatic Speech Recognition in Multi-party Meetings
Mohan Shi, Jie Zhang, Zhihao Du +4
Speaker-attributed automatic speech recognition (SA-ASR) in multi-party meeting scenarios is one of the most valuable and challenging ASR task. It was shown that single-channel fra…
Robust Data2vec: Noise-robust Speech Representation Learning for ASR by Combining Regression and Improved Contrastive Learning
Qiu-Shi Zhu, Long Zhou, Jie Zhang +3
Self-supervised pre-training methods based on contrastive learning or regression tasks can utilize more unlabeled data to improve the performance of automatic speech recognition (A…
Speech Enhancement Using Self-Supervised Pre-Trained Model and Vector Quantization
Xiao-Ying Zhao, Qiu-Shi Zhu, Jie Zhang
With the development of deep learning, neural network-based speech enhancement (SE) models have shown excellent performance. Meanwhile, it was shown that the development of self-su…
Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning
Rongkai Zhang, Cong Zhang, Zhiguang Cao +5
We propose a manager-worker framework based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), \ie~multiple-vehicle TSP wi…
Multi-modal Transformer Path Prediction for Autonomous Vehicle
Chia Hong Tseng, Jie Zhang, Min-Te Sun +2
Reasoning about vehicle path prediction is an essential and challenging problem for the safe operation of autonomous driving systems. There exist many research works for path predi…
Microwave QR Code: An IRS-Based Solution
Sai Xu, Yanan Du, Jiliang Zhang +1
This letter proposes to employ intelligent reflecting surface (IRS) as an information media to display a microwave quick response (QR) code for Internet-of-Things applications. To…
Fed-FSNet: Mitigating Non-I.I.D. Federated Learning via Fuzzy Synthesizing Network
Jingcai Guo, Song Guo, Jie Zhang +1
Federated learning (FL) has emerged as a promising privacy-preserving distributed machine learning framework recently. It aims at collaboratively learning a shared global model by…
An IRS Backscatter Enabled Integrated Sensing, Communication and Computation System
Sai Xu, Yanan Du, Jiliang Zhang +2
This paper proposes to leverage intelligent reflecting surface (IRS) backscatter to realize radio-frequency-chain-free uplink-transmissions (RFCF-UT). In this communication paradig…
On the Performance of Data Compression in Clustered Fog Radio Access Networks
Haonan Hu, Yan Jiang, Jiliang Zhang +3
The fog-radio-access-network (F-RAN) has been proposed to address the strict latency requirements, which offloads computation tasks generated in user equipments (UEs) to the edge t…
Multivariate Sparse Group Lasso Joint Model for Radiogenomics Data
Tiantian Zeng, Md Selim, Jie Zhang +3
Radiogenomics is an emerging field in cancer research that combines medical imaging data with genomic data to predict patients clinical outcomes. In this paper, we propose a multiv…
A characterization of rich c-partite (c > 7) tournaments without (c + 2)-cycles
Jie Zhang, Zhilan Wang, Jin Yan
Let c be an integer. A c-partite tournament is an orientation of a complete c-partite graph. A c-partite tournament is rich if it is strong, and each partite set has at least two v…
Joint Training of Speech Enhancement and Self-supervised Model for Noise-robust ASR
Qiu-Shi Zhu, Jie Zhang, Zi-Qiang Zhang +1
Speech enhancement (SE) is usually required as a front end to improve the speech quality in noisy environments, while the enhanced speech might not be optimal for automatic speech…
Layer-wised Model Aggregation for Personalized Federated Learning
Xiaosong Ma, Jie Zhang, Song Guo +1
Personalized Federated Learning (pFL) not only can capture the common priors from broad range of distributed data, but also support customized models for heterogeneous clients. Res…
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems
Yuanxing Zhang, Langshi Chen, Siran Yang +12
The development of personalized recommendation has significantly improved the accuracy of information matching and the revenue of e-commerce platforms. Recently, it has 2 trends: 1…
Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression
Feijie Wu, Shiqi He, Song Guo +4
Traditional one-bit compressed stochastic gradient descent can not be directly employed in multi-hop all-reduce, a widely adopted distributed training paradigm in network-intensive…