210 citations · 1.8k across the 103 of their papers we have counts for
102 papers
Rep2wav: Noise Robust text-to-speech Using self-supervised representations
Qiushi Zhu, Yu Gu, Rilin Chen +4
Benefiting from the development of deep learning, text-to-speech (TTS) techniques using clean speech have achieved significant performance improvements. The data collected from rea…
Overlap Bias Matching is Necessary for Point Cloud Registration
Pengcheng Shi, Jie Zhang, Haozhe Cheng +4
Point cloud registration is a fundamental problem in many domains. Practically, the overlap between point clouds to be registered may be relatively small. Most unsupervised methods…
On the Manipulability of Maximum Vertex-Weighted Bipartite -matching Mechanisms
Gennaro Auricchio, Jie Zhang
In this paper, we study the Maximum Vertex-weighted -Matching (MVbM) problem on bipartite graphs in a new game-theoretical environment. In contrast to other game-theoretical set…
That's BAD: Blind Anomaly Detection by Implicit Local Feature Clustering
Jie Zhang, Masanori Suganuma, Takayuki Okatani
Recent studies on visual anomaly detection (AD) of industrial objects/textures have achieved quite good performance. They consider an unsupervised setting, specifically the one-cla…
Contextual Affinity Distillation for Image Anomaly Detection
Jie Zhang, Masanori Suganuma, Takayuki Okatani
Previous works on unsupervised industrial anomaly detection mainly focus on local structural anomalies such as cracks and color contamination. While achieving significantly high de…
Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
Sikai Bai, Shuaicheng Li, Weiming Zhuang +7
Federated learning has become a popular method to learn from decentralized heterogeneous data. Federated semi-supervised learning (FSSL) emerges to train models from a small fracti…
Towards Omni-generalizable Neural Methods for Vehicle Routing Problems
Jianan Zhou, Yaoxin Wu, Wen Song +2
Learning heuristics for vehicle routing problems (VRPs) has gained much attention due to the less reliance on hand-crafted rules. However, existing methods are typically trained an…
On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions
Leijie Wu, Song Guo, Junxiao Wang +3
As Federated Learning (FL) has gained increasing attention, it has become widely acknowledged that straightforwardly applying stochastic gradient descent (SGD) on the overall frame…
Federated Generative Learning with Foundation Models
Jie Zhang, Xiaohua Qi, Bo Zhao
Existing approaches in Federated Learning (FL) mainly focus on sending model parameters or gradients from clients to a server. However, these methods are plagued by significant ine…
Eeg2vec: Self-Supervised Electroencephalographic Representation Learning
Qiushi Zhu, Xiaoying Zhao, Jie Zhang +3
Recently, many efforts have been made to explore how the brain processes speech using electroencephalographic (EEG) signals, where deep learning-based approaches were shown to be a…
CASA-ASR: Context-Aware Speaker-Attributed ASR
Mohan Shi, Zhihao Du, Qian Chen +5
Recently, speaker-attributed automatic speech recognition (SA-ASR) has attracted a wide attention, which aims at answering the question ``who spoke what''. Different from modular s…
Semantic VAD: Low-Latency Voice Activity Detection for Speech Interaction
Mohan Shi, Yuchun Shu, Lingyun Zuo +4
For speech interaction, voice activity detection (VAD) is often used as a front-end. However, traditional VAD algorithms usually need to wait for a continuous tail silence to reach…
BASEN: Time-Domain Brain-Assisted Speech Enhancement Network with Convolutional Cross Attention in Multi-talker Conditions
Jie Zhang, Qing-Tian Xu, Qiu-Shi Zhu +1
Time-domain single-channel speech enhancement (SE) still remains challenging to extract the target speaker without any prior information on multi-talker conditions. It has been sho…
Security Enhancement of Quantum Noise Stream Cipher Based on Probabilistic Constellation Shaping
Sheng Liu, Shuang Wei, Wei Wang +10
We propose a QNSC pre-coding scheme based on probabilistic shaping of the basis, to reduce the probability of ciphertext bits that are easier to be intercepted. Experiment results…
Towards Unbiased Training in Federated Open-world Semi-supervised Learning
Jie Zhang, Xiaosong Ma, Song Guo +1
Federated Semi-supervised Learning (FedSSL) has emerged as a new paradigm for allowing distributed clients to collaboratively train a machine learning model over scarce labeled dat…
Analytic Network Traffic Prediction Based on User Behavior Modeling
Liangzhi Wang, Jiliang Zhang, Zitian Zhang +1
This paper proposes an interpretable user-behavior-based (UBB) network traffic prediction (NTP) method. Based on user behavior, a weekly traffic demand profile can be naturally sor…
Prophet: Conflict-Free Sharding Blockchain via Byzantine-Tolerant Deterministic Ordering
Zicong Hong, Song Guo, Enyuan Zhou +5
Sharding scales throughput by splitting blockchain nodes into parallel groups. However, different shards' independent and random scheduling for cross-shard transactions results in…
Spatial Scattering Modulation with Multipath Component Aggregation Based on Antenna Arrays
Jiliang Zhang, Wei Liu, Alan Tennant +3
In this paper, a multipath component aggregation (MCA) mechanism is introduced for spatial scattering modulation (SSM) to overcome the limitation in conventional SSM that the trans…
Neural Airport Ground Handling
Yaoxin Wu, Jianan Zhou, Yunwen Xia +3
Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics o…
AMPLE: An Adaptive Multiple Path Loss Exponent Radio Propagation Model Considering Environmental Factors
Lingyou Zhou, Jie Zhang, Jiliang Zhang +2
We present AMPLE -- a novel multiple path loss exponent (PLE) radio propagation model that can adapt to different environmental factors. The proposed model aims at accurately predi…
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling
Jianan Zhou, Yaoxin Wu, Zhiguang Cao +3
Dispatching vehicle fleets to serve flights is a key task in airport ground handling (AGH). Due to the notable growth of flights, it is challenging to simultaneously schedule multi…
Speech Enhancement with Multi-granularity Vector Quantization
Xiao-Ying Zhao, Qiu-Shi Zhu, Jie Zhang
With advances in deep learning, neural network based speech enhancement (SE) has developed rapidly in the last decade. Meanwhile, the self-supervised pre-trained model and vector q…
TAPAS: Fast and Automatic Derivation of Tensor Parallel Strategies for Large Neural Networks
Ziji Shi, Le Jiang, Ang Wang +6
Tensor parallelism is an essential technique for distributed training of large neural networks. However, automatically determining an optimal tensor parallel strategy is challengin…
An optimized online filter stack spectrometer
Jia-xing Wen, Ge Ma, Ming-hai Yu +17
The spectrum of laser-plasma-generated X-rays is very important as it can characterize electron dynamics and also be useful for applications, and nowadays with the forthcoming high…