no code implementations • 4 Sep 2024 • Guanwen Xie, Jingzehua Xu, Yiyuan Yang, Yimian Ding, Shuai Zhang
Achieving the effective design and improvement of reward functions in reinforcement learning (RL) tasks with complex custom environments and multiple requirements presents considerable challenges.
Long-Context Understanding
Multi-Objective Reinforcement Learning
+1
no code implementations • 4 Sep 2024 • Jingzehua Xu, Yimian Ding, Yiyuan Yang, Guanwen Xie, Shuai Zhang
However, underwater tasks have mostly failed due to the observation delay caused by acoustic communication in the Internet of underwater things.
no code implementations • 15 Jul 2024 • Yiyuan Yang, Zheshun Wu, Yong Chu, Zhenghua Chen, Zenglin Xu, Qingsong Wen
Process mining, as a high-level field in data mining, plays a crucial role in enhancing operational efficiency and decision-making across organizations.
4 code implementations • 18 Jun 2024 • Wenjie Du, Jun Wang, Linglong Qian, Yiyuan Yang, Zina Ibrahim, Fanxing Liu, Zepu Wang, Haoxin Liu, Zhiyuan Zhao, Yingjie Zhou, Wenjia Wang, Kaize Ding, Yuxuan Liang, B. Aditya Prakash, Qingsong Wen
Despite the development of numerous deep learning algorithms for time series imputation, the community lacks standardized and comprehensive benchmark platforms to effectively evaluate imputation performance across different settings.
no code implementations • 11 Jun 2024 • Yiyuan Yang, Niki Trigoni, Andrew Markham
Speech enhancement significantly improves the clarity and intelligibility of speech in noisy environments, improving communication and listening experiences.
1 code implementation • 28 May 2024 • Ziqi Zhang, Zifeng Zhuang, Jingzehua Xu, Yiyuan Yang, Yubo Huang, Donglin Wang, Shuai Zhang
Specifically, ADR addresses several limitations in previous IL algorithms: First, most IL algorithms are based on the Bellman operator, which inevitably suffer from cumulative offsets from sub-optimal rewards during multi-step update processes.
1 code implementation • 26 May 2024 • Linglong Qian, Yiyuan Yang, Wenjie Du, Jun Wang, Zina Ibrahim
Time series imputation is a critical challenge in data mining, particularly in domains like healthcare and environmental monitoring, where missing data can compromise analytical outcomes.
1 code implementation • 29 Apr 2024 • Yiyuan Yang, Ming Jin, Haomin Wen, Chaoli Zhang, Yuxuan Liang, Lintao Ma, Yi Wang, Chenghao Liu, Bin Yang, Zenglin Xu, Jiang Bian, Shirui Pan, Qingsong Wen
Conditioned models, on the other hand, utilize extra information to enhance performance and are similarly divided for both predictive and generative tasks.
1 code implementation • 17 Apr 2024 • Zahra Zamanzadeh Darban, Yiyuan Yang, Geoffrey I. Webb, Charu C. Aggarwal, Qingsong Wen, Mahsa Salehi
To address this limitation, we propose a novel Domain Adaptation Contrastive learning model for Anomaly Detection in multivariate time series (DACAD), combining UDA with contrastive learning.
1 code implementation • 28 Mar 2024 • Yiyuan Yang, Guodong Long, Tao Shen, Jing Jiang, Michael Blumenstein
By co-working with a foundation model, a global adapter and a local adapter jointly tackle the test-time distribution shifts and client-specific personalization.
1 code implementation • 18 Jan 2024 • Zhijie Zhong, Zhiwen Yu, Yiyuan Yang, Weizheng Wang, Kaixiang Yang
Anomaly detection in time series analysis is a pivotal task, yet it poses the challenge of discerning normal and abnormal patterns in label-deficient scenarios.
no code implementations • 18 Dec 2023 • Chengyuan Zhu, Yiyuan Yang, Kaixiang Yang, Haifeng Zhang, Qinmin Yang, C. L. Philip Chen
This refinement is crucial in effectively identifying genuine threats to pipelines, thus enhancing the safety of energy transportation.
1 code implementation • NeurIPS 2023 • Kaichen Zhou, Jia-Xing Zhong, Sangyun Shin, Kai Lu, Yiyuan Yang, Andrew Markham, Niki Trigoni
The introduction of neural radiance fields has greatly improved the effectiveness of view synthesis for monocular videos.
2 code implementations • 17 Jun 2023 • Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
On the other hand, contrastive learning aims to find a representation that can clearly distinguish any instance from the others, which can bring a more natural and promising representation for time series anomaly detection.
1 code implementation • 7 Apr 2023 • Yiyuan Yang, Rongshang Li, Qiquan Shi, Xijun Li, Gang Hu, Xing Li, Mingxuan Yuan
This paper proposes a novel Stream-Graph neural network-based Data Prefetcher (SGDP).
no code implementations • 14 Apr 2021 • Yiyuan Yang, Kenneth Li, Fernanda Eliott, Maithilee Kunda
People's visual experiences of the world are easy to carve up and examine along natural language boundaries, e. g., by category labels, attribute labels, etc.
1 code implementation • 16 Dec 2019 • Yiyuan Yang, Riqiang Gao, Yucheng Tang, Sanja L. Antic, Steve Deppen, Yuankai Huo, Kim L. Sandler, Pierre P. Massion, Bennett A. Landman
To improve performance on the primary task, we propose an Internal-Transfer Weighting (ITW) strategy to suppress the loss functions on auxiliary tasks for the final stages of training.