no code implementations • 21 Apr 2024 • Donghuo Zeng, Yanan Wang, Kazushi Ikeda, Yi Yu
However, the model training fails to fully explore the space due to the scarcity of training data points, resulting in an incomplete representation of the overall positive and negative distributions.
1 code implementation • 15 Apr 2024 • Shuaicong Hu, Yanan Wang, Jian Liu, Jingyu Lin, Shengmei Qin, Zhenning Nie, Zhifeng Yao, Wenjie Cai, Cuiwei Yang
Considering the variability of amplitude and phase patterns in electrocardiogram (ECG) signals due to cardiac activity and individual differences, existing entropy-based studies have not fully utilized these two patterns and lack integration.
no code implementations • 6 Jan 2024 • Paridhi Maheshwari, Hongyu Ren, Yanan Wang, Rok Sosic, Jure Leskovec
The results demonstrate both robustness and efficiency of TimeGraphs on a range of temporal reasoning tasks.
no code implementations • 27 Sep 2023 • Yanan Wang, Donghuo Zeng, Shinya Wada, Satoshi Kurihara
In this work, to achieve high efficiency-performance multimodal transfer learning, we propose VideoAdviser, a video knowledge distillation method to transfer multimodal knowledge of video-enhanced prompts from a multimodal fundamental model (teacher) to a specific modal fundamental model (student).
no code implementations • 4 Sep 2023 • Rui Wang, Xing Liu, Yanan Wang, Haiping Huang
The recently released artificial intelligence conversational agent, ChatGPT, has gained significant attention in academia and real life.
no code implementations • 22 Feb 2023 • Donghuo Zeng, Jianming Wu, Yanan Wang, Kazunori Matsumoto, Gen Hattori, Kazushi Ikeda
Furthermore, our proposed topic-switch algorithm achieves an average score of 1. 767 and outperforms PLATO-JDS by 0. 267, indicating its effectiveness in improving the user experience of our system.
1 code implementation • 1 Feb 2023 • Monisha Singh, Ximi Hoque, Donghuo Zeng, Yanan Wang, Kazushi Ikeda, Abhinav Dhall
The experiments show the usefulness of the proposed dataset.
no code implementations • 7 Nov 2022 • Donghuo Zeng, Yanan Wang, Jianming Wu, Kazushi Ikeda
In this paper, to reduce the interference of hard negative samples in representation learning, we propose a new AV-CMR model to optimize semantic features by directly predicting labels and then measuring the intrinsic correlation between audio-visual data using complete cross-triple loss.
no code implementations • ICCV 2023 • Yanan Wang, Michihiro Yasunaga, Hongyu Ren, Shinya Wada, Jure Leskovec
Visual question answering (VQA) requires systems to perform concept-level reasoning by unifying unstructured (e. g., the context in question and answer; "QA context") and structured (e. g., knowledge graph for the QA context and scene; "concept graph") multimodal knowledge.
2 code implementations • CVPR 2022 • Yanan Wang, Xuezhi Liang, Shengcai Liao
To address this, in this work, an automatic approach is proposed to directly clone the whole outfits from real-world person images to virtual 3D characters, such that any virtual person thus created will appear very similar to its real-world counterpart.
Ranked #1 on Unsupervised Domain Adaptation on ClonedPerson (using extra training data)
Generalizable Person Re-identification Unsupervised Domain Adaptation +1
no code implementations • 1 Feb 2022 • Dadong Miao, Yanan Wang, Guoyu Tang, Lin Liu, Sulong Xu, Bo Long, Yun Xiao, Lingfei Wu, Yunjiang Jiang
Recent years have seen a significant amount of interests in Sequential Recommendation (SR), which aims to understand and model the sequential user behaviors and the interactions between users and items over time.
no code implementations • 28 Jan 2022 • Haowei He, Jingzhao Zhang, Yanan Wang, Benben Jiang, Shaobo Huang, Chen Wang, Yang Zhang, Gengang Xiong, Xuebing Han, Dongxu Guo, Guannan He, Minggao Ouyang
In addition to demonstrating how existing deep learning algorithms can be applied to this task, we further develop an algorithm that exploits the data structure of battery systems.
no code implementations • 4 Dec 2020 • Yanan Wang, Yong Ge, Li Li, Rui Chen, Tong Xu
To improve adaptation efficiency, we learn to recover the user policy and reward from only a few interactions via an inverse reinforcement learning method to assist a meta-level recommendation agent.
Model-based Reinforcement Learning Recommendation Systems +2
1 code implementation • 23 Jun 2020 • Yanan Wang, Shengcai Liao, Ling Shao
To address this, we propose to automatically synthesize a large-scale person re-identification dataset following a set-up similar to real surveillance but with virtual environments, and then use the synthesized person images to train a generalizable person re-identification model.
Domain Generalization Generalizable Person Re-identification +1
no code implementations • 28 Aug 2019 • Yanan Wang, Tong Xu, Xin Niu, Chang Tan, Enhong Chen, Hui Xiong
Moreover, based on the temporally-dependent traffic information, we design a Graph Neural Network based model to represent relationships among multiple traffic lights, and the decision for each traffic light will be made in a distributed way by the deep Q-learning method.