no code implementations • 17 Jan 2024 • Depeng Li, Tianqi Wang, Junwei Chen, Qining Ren, Kenji Kawaguchi, Zhigang Zeng
Deep neural networks are susceptible to catastrophic forgetting when trained on sequential tasks.
no code implementations • 26 Sep 2023 • Yuanzheng Li, Xinxin Long, Yang Li, Yizhou Ding, Tao Yang, Zhigang Zeng
In this context, unreasonable profit distributions on the demand-supply side would lead to the conflict of interests and diminish the effectiveness of cooperative responses.
no code implementations • 12 Aug 2023 • Jiang Li, XiaoPing Wang, Yingjian Liu, Zhigang Zeng
We utilize TE and SE to combine the strengths of previous methods in a simplistic manner to efficiently capture temporal and spatial contextual information in the conversation.
1 code implementation • 28 Jul 2023 • Jiang Li, XiaoPing Wang, Yingjian Liu, Zhigang Zeng
RUME is applied to extract conversation-level contextual emotional cues while pulling together data distributions between modalities; ACME is utilized to perform multimodal interaction centered on textual modality; LESM is used to model emotion shift and capture emotion-shift information, thereby guiding the learning of the main task.
Ranked #8 on Emotion Recognition in Conversation on IEMOCAP
Emotion Recognition in Conversation Multimodal Emotion Recognition
no code implementations • 2 Jul 2023 • Jiang Li, XiaoPing Wang, Zhigang Zeng
How to model the context in a conversation is a central aspect and a major challenge of ERC tasks.
no code implementations • 21 Jun 2023 • Depeng Li, Zhigang Zeng
The inaccessibility of historical data is tackled by holistically controlling the parameters of a well-trained model, ensuring that the decision boundary learned fits new classes while retaining recognition of previously learned classes.
no code implementations • 18 Jun 2023 • Depeng Li, Tianqi Wang, Bingrong Xu, Kenji Kawaguchi, Zhigang Zeng, Ponnuthurai Nagaratnam Suganthan
Continual learning can incrementally absorb new concepts without interfering with previously learned knowledge.
no code implementations • 16 Jun 2023 • Depeng Li, Tianqi Wang, Junwei Chen, Kenji Kawaguchi, Cheng Lian, Zhigang Zeng
Multi-view learning (MVL) has gained great success in integrating information from multiple perspectives of a dataset to improve downstream task performance.
no code implementations • 3 Jun 2023 • Fusheng Yu, XiaoPing Wang, Jiang Li, Shaojin Wu, Junjie Zhang, Zhigang Zeng
However, limited availability of high-quality datasets has hindered the development of deep learning methods for safety clothing and helmet detection.
1 code implementation • 20 Mar 2023 • Yingjian Liu, Jiang Li, XiaoPing Wang, Zhigang Zeng
Emotion Recognition in Conversation (ERC) has attracted growing attention in recent years as a result of the advancement and implementation of human-computer interface technologies.
Ranked #5 on Emotion Recognition in Conversation on EmoryNLP
no code implementations • CVPR 2023 • Haozhao Wang, Yichen Li, Wenchao Xu, Ruixuan Li, Yufeng Zhan, Zhigang Zeng
In this paper, we propose a new perspective that treats the local data in each client as a specific domain and design a novel domain knowledge aware federated distillation method, dubbed DaFKD, that can discern the importance of each model to the distillation sample, and thus is able to optimize the ensemble of soft predictions from diverse models.
no code implementations • ICCV 2023 • ShouWen Wang, Qian Wan, Xiang Xiang, Zhigang Zeng
In this paper, we propose saliency regularization (SR) for a novel self-training framework.
no code implementations • 29 Dec 2022 • Yuanzheng Li, Shangyang He, Yang Li, Yang Shi, Zhigang Zeng
Then, these local models are periodically uploaded to a server and their parameters are aggregated to build a global agent, which will be broadcasted to MGs and replace their local agents.
no code implementations • 13 Dec 2022 • Guoqing Lv, Jiang Li, XiaoPing Wang, Zhigang Zeng
We separately encode the last utterance and fuse it with the entire dialogue through the multi-head attention based intention fusion module to capture the speaker's intention.
1 code implementation • 6 Jul 2022 • Jiang Li, XiaoPing Wang, Guoqing Lv, Zhigang Zeng
In multimodal ERC, GNNs are capable of extracting both long-distance contextual information and inter-modal interactive information.
Ranked #19 on Emotion Recognition in Conversation on IEMOCAP
Emotion Classification Emotion Recognition in Conversation +1
no code implementations • 17 Apr 2022 • Yuanzheng Li, Shangyang He, Yang Li, Leijiao Ge, Suhua Lou, Zhigang Zeng
This paper tackles this issue by proposing a reinforcement learning assisted deep learning framework for the probabilistic EVCS charging power forecasting to capture its uncertainties.
no code implementations • 10 Jan 2022 • Jiahao Zheng, Sen Zhang, XiaoPing Wang, Zhigang Zeng
Multimodal sentiment analysis (MSA) is a fundamental complex research problem due to the heterogeneity gap between different modalities and the ambiguity of human emotional expression.
no code implementations • 30 Oct 2020 • Lubin Meng, Jian Huang, Zhigang Zeng, Xue Jiang, Shan Yu, Tzyy-Ping Jung, Chin-Teng Lin, Ricardo Chavarriaga, Dongrui Wu
Test samples with the backdoor key will then be classified into the target class specified by the attacker.
1 code implementation • 3 Jul 2020 • Dongrui Wu, Xue Jiang, Ruimin Peng, Wanzeng Kong, Jian Huang, Zhigang Zeng
Transfer learning (TL) has been widely used in motor imagery (MI) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promising performance.
no code implementations • 25 Mar 2019 • Dongrui Wu, Chin-Teng Lin, Jian Huang, Zhigang Zeng
Fuzzy systems have achieved great success in numerous applications.