no code implementations • 24 Apr 2024 • Linyu Liu, Yu Pan, Xiaocheng Li, Guanting Chen
Large language models (LLMs) are highly capable of many tasks but they can sometimes generate unreliable or inaccurate outputs.
no code implementations • 3 Apr 2024 • Yu Pan, Lei Ma, Jianjun Zhao
Neural speech codec has recently gained widespread attention in generative speech modeling domains, like voice conversion, text-to-speech synthesis, etc.
no code implementations • 1 Feb 2024 • Maolin Wang, Yu Pan, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao, Wanyu Wang, Yiqi Wang, Zitao Liu, Langming Liu
Our contributions encompass the introduction of a pioneering CDF-based TPP model, the development of a methodology for incorporating past event information into future event prediction, and empirical validation of CuFun's effectiveness through extensive experimentation on synthetic and real-world datasets.
1 code implementation • 17 Jan 2024 • Yu Pan, Ye Yuan, Yichun Yin, Jiaxin Shi, Zenglin Xu, Ming Zhang, Lifeng Shang, Xin Jiang, Qun Liu
The rapid progress of Transformers in artificial intelligence has come at the cost of increased resource consumption and greenhouse gas emissions due to growing model sizes.
no code implementations • 7 Nov 2023 • Yu Pan, Jianxin Sun, Hongfeng Yu, Geng Bai, Yufeng Ge, Joe Luck, Tala Awada
At the same time, the sheer amount of data poses a great challenge to data storage and analysis, and the \textit{de facto} data management and analysis practices adopted by scientists have become increasingly inefficient.
no code implementations • 9 Oct 2023 • Xin Liu, Wei Li, Dazhi Zhan, Yu Pan, Xin Ma, Yu Ding, Zhisong Pan
Federated learning (FL) is a widely employed distributed paradigm for collaboratively training machine learning models from multiple clients without sharing local data.
no code implementations • 4 Oct 2023 • Dun Zeng, Zenglin Xu, Yu Pan, Xu Luo, Qifan Wang, Xiaoying Tang
Central to this process is the technique of unbiased client sampling, which ensures a representative selection of clients.
1 code implementation • 4 Oct 2023 • Dun Zeng, Zenglin Xu, Yu Pan, Qifan Wang, Xiaoying Tang
The combined effects of statistical and system heterogeneity can significantly reduce the efficiency of federated optimization.
no code implementations • 17 Sep 2023 • Jixun Yao, Yuguang Yang, Yi Lei, Ziqian Ning, Yanni Hu, Yu Pan, JingJing Yin, Hongbin Zhou, Heng Lu, Lei Xie
In this study, we propose PromptVC, a novel style voice conversion approach that employs a latent diffusion model to generate a style vector driven by natural language prompts.
no code implementations • 8 Aug 2023 • Yu Pan, Yuguang Yang, Yuheng Huang, Jixun Yao, JingJing Yin, Yanni Hu, Heng Lu, Lei Ma, Jianjun Zhao
Despite notable progress, speech emotion recognition (SER) remains challenging due to the intricate and ambiguous nature of speech emotion, particularly in wild world.
no code implementations • 14 Jul 2023 • Gongxin Yao, Yixin Xuan, YiWei Chen, Yu Pan
Image-to-point cloud registration aims to determine the relative camera pose between an RGB image and a reference point cloud, serving as a general solution for locating 3D objects from 2D observations.
no code implementations • 13 Jun 2023 • Yu Pan, Yanni Hu, Yuguang Yang, Wen Fei, Jixun Yao, Heng Lu, Lei Ma, Jianjun Zhao
Contrastive cross-modality pretraining has recently exhibited impressive success in diverse fields, whereas there is limited research on their merits in speech emotion recognition (SER).
no code implementations • 5 Jun 2023 • Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao
THNN is a faithful hypergraph modeling framework through high-order outer product feature message passing and is a natural tensor extension of the adjacency-matrix-based graph neural networks.
1 code implementation • 15 Mar 2023 • Yuguang Yang, Yu Pan, JingJing Yin, Jiangyu Han, Lei Ma, Heng Lu
SqueezeFormer has recently shown impressive performance in automatic speech recognition (ASR).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 3 Mar 2023 • YiWei Chen, Chen Jiang, Yu Pan
Single-Photon Image Super-Resolution (SPISR) aims to recover a high-resolution volumetric photon counting cube from a noisy low-resolution one by computational imaging algorithms.
1 code implementation • 22 Jan 2023 • Maolin Wang, Yu Pan, Zenglin Xu, Xiangli Yang, Guangxi Li, Andrzej Cichocki
Interestingly, although these two types of networks originate from different observations, they are inherently linked through the common multilinearity structure underlying both TNs and NNs, thereby motivating a significant number of intellectual developments regarding combinations of TNs and NNs.
1 code implementation • 5 Dec 2022 • Yuguang Yang, Yu Pan, JingJing Yin, Heng Lu
This paper proposes a Learnable Multiplicative absolute position Embedding based Conformer (LMEC).
1 code implementation • 28 May 2022 • Yu Pan, Zeyong Su, Ao Liu, Jingquan Wang, Nannan Li, Zenglin Xu
To address this problem, we propose a universal weight initialization paradigm, which generalizes Xavier and Kaiming methods and can be widely applicable to arbitrary TCNNs.
no code implementations • 23 May 2022 • Lei Zhang, Yu Pan, Yi Liu, Qibin Zheng, Zhisong Pan
In order to improve the defense ability of defender, a game model based on reward randomization reinforcement learning is proposed.
no code implementations • 16 May 2022 • Lei Zhang, Yu Pan, Yi Liu, Qibin Zheng, Zhisong Pan
Following that, we proposed a user's permissions reasoning method based on reinforcement learning.
no code implementations • 17 Feb 2022 • Jingquan Wang, Jing Xu, Yu Pan, Zenglin Xu
Few-shot learning aims to classify unseen classes with only a limited number of labeled data.
2 code implementations • 7 Jan 2022 • YiWei Chen, Gongxin Yao, Yong liu, Hongye Su, Xiaomin Hu, Yu Pan
Photon-efficient imaging with the single-photon light detection and ranging (LiDAR) captures the three-dimensional (3D) structure of a scene by only a few detected signal photons per pixel.
2 code implementations • 5 Jan 2022 • Gongxin Yao, YiWei Chen, Yong liu, Xiaomin Hu, Yu Pan
Single-photon light detection and ranging (LiDAR) has been widely applied to 3D imaging in challenging scenarios.
no code implementations • 16 Nov 2021 • Yu Pan, Kwo-Sen Kuo, Michael L. Rilee, Hongfeng Yu
Deep Neural Networks (DNNs) have performed admirably in classification tasks.
no code implementations • 18 Oct 2021 • Langzhang Liang, Cuiyun Gao, Shiyi Chen, Shishi Duan, Yu Pan, Junjin Zheng, Lei Wang, Zenglin Xu
Graph Convolutional Networks (GCNs) are powerful for processing graph-structured data and have achieved state-of-the-art performance in several tasks such as node classification, link prediction, and graph classification.
no code implementations • 18 Sep 2021 • Yuguang Yang, Yu Pan, Xin Dong, Minqiang Xu
Second, we design a novel model inference scheme based on RepVGG which can efficiently improve the QbE search quality.
1 code implementation • 19 Aug 2021 • YiWei Chen, Yu Pan, Daoyi Dong
We prove that such a rule is much more relaxed than that of TT, which means ResTT can easily address the vanishing and exploding gradient problem that exists in the existing TT models.
no code implementations • 10 May 2021 • Xinglin Pan, Jing Xu, Yu Pan, Liangjian Wen, WenXiang Lin, Kun Bai, Zenglin Xu
Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks including image classification.
1 code implementation • 11 Apr 2021 • Yu Pan, Maolin Wang, Zenglin Xu
Tensor Decomposition Networks (TDNs) prevail for their inherent compact architectures.
1 code implementation • 8 Mar 2021 • YiWei Chen, Yu Pan, Guofeng Zhang, Shuming Cheng
Quantum properties, such as entanglement and coherence, are indispensable resources in various quantum information processing tasks.
no code implementations • 25 Jan 2021 • Shibo Zhou, Yu Pan
Since time series always contains a lot of noise, which has a negative impact on network training, people usually filter the original data before training the network.
14 code implementations • 3 Jan 2021 • Jing Xu, Yu Pan, Xinglin Pan, Steven Hoi, Zhang Yi, Zenglin Xu
The ResNet and its variants have achieved remarkable successes in various computer vision tasks.
Ranked #3 on Medical Image Classification on NCT-CRC-HE-100K
no code implementations • 1 Jan 2021 • Xinglin Pan, Jing Xu, Yu Pan, WenXiang Lin, Liangjian Wen, Zenglin Xu
Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks, e. g., image classification.
no code implementations • 22 Sep 2020 • Nannan Li, Yu Pan, Yaran Chen, Zixiang Ding, Dongbin Zhao, Zenglin Xu
Interestingly, we discover that part of the rank elements is sensitive and usually aggregate in a narrow region, namely an interest region.
no code implementations • 23 Aug 2020 • Yi-Wei Chen, Yu Pan, Daoyi Dong
Quantum Language Models (QLMs) in which words are modelled as quantum superposition of sememes have demonstrated a high level of model transparency and good post-hoc interpretability.
2 code implementations • 8 Jul 2020 • Junhua Zou, Yexin Duan, Boyu Li, Wu Zhang, Yu Pan, Zhisong Pan
Fast gradient sign attack series are popular methods that are used to generate adversarial examples.
15 code implementations • CVPR 2020 • Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, Oscar Beijbom
Most autonomous vehicles, however, carry a combination of cameras and range sensors such as lidar and radar.
Ranked #312 on 3D Object Detection on nuScenes (using extra training data)
1 code implementation • NIPS Workshop CDNNRIA 2018 • Yu Pan, Jing Xu, Maolin Wang, Jinmian Ye, Fei Wang, Kun Bai, Zenglin Xu
Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in sequential data modeling.