Dai Liu

According to our database, Dai Liu authored at least 12 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2025

DD-Ranking: Rethinking the Evaluation of Dataset Distillation.

Zekai Li, Xinhao Zhong, Samir Khaki, Zhiyuan Liang, Yuhao Zhou, Mingjia Shi, Ziqiao Wang, Xuanlei Zhao, Wangbo Zhao, Ziheng Qin, Mengxuan Wu, Pengfei Zhou, Haonan Wang, David Junhao Zhang, Jia-Wei Liu, Shaobo Wang, Dai Liu, Linfeng Zhang, Guang Li, Kun Wang, Zheng Zhu, Zhiheng Ma, Joey Tianyi Zhou, Jiancheng Lv, Yaochu Jin, Peihao Wang, Kaipeng Zhang, Lingjuan Lyu, Yiran Huang, Zeynep Akata, Zhiwei Deng, Xindi Wu, George Cazenavette, Yuzhang Shang, Justin Cui, Jindong Gu, Qian Zheng, Hao Ye, Shuo Wang, Xiaobo Wang, Yan Yan, Angela Yao, Mike Zheng Shou, Tianlong Chen, Hakan Bilen, Baharan Mirzasoleiman, Manolis Kellis, Konstantinos N. Plataniotis, Zhangyang Wang, Bo Zhao, Yang You, Kai Wang

CoRR, May, 2025

KLiNQ: Knowledge Distillation-Assisted Lightweight Neural Network for Qubit Readout on FPGA.

Xiaorang Guo, Tigran Bunarjyan, Dai Liu, Benjamin Lienhard, Martin Schulz

CoRR, March, 2025

2024

Reinforcement Learning-Driven Co-Scheduling and Diverse Resource Assignments on NUMA Systems.

Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz

Proceedings of the 42nd IEEE International Conference on Computer Design, 2024

Dataset Distillation by Automatic Training Trajectories.

Dai Liu, Jindong Gu, Hu Cao, Carsten Trinitis, Martin Schulz

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

The impact of digital supply chain capabilities on enterprise sustainable competitive performance: an ambidextrous view.

Ning Li, Dai Liu, Francis Boadu

Ind. Manag. Data Syst., 2023

Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments.

Rui Song, Dai Liu, Dave Zhenyu Chen, Andreas Festag, Carsten Trinitis, Martin Schulz, Alois Knoll

Proceedings of the International Joint Conference on Neural Networks, 2023

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach.

Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz

Proceedings of the IEEE International Conference on Cluster Computing, 2023

2022

Orchestrated Co-scheduling, Resource Partitioning, and Power Capping on CPU-GPU Heterogeneous Systems via Machine Learning.

Issa Saba, Eishi Arima, Dai Liu, Martin Schulz

Proceedings of the Architecture of Computing Systems - 35th International Conference, 2022

2020

Target tracking methods based on a signal-to-noise ratio model.

Dai Liu, Yong-Bo Zhao, Ziqian Yuan, Jie-tao Li, Guo-ji Chen

Frontiers Inf. Technol. Electron. Eng., 2020

2019

Tracking Algorithms Aided by the Pose of Target.

Dai Liu, Yongbo Zhao, Baoqing Xu

IEEE Access, 2019

2018

Green Supplier Selection for Process Industries Using Weighted Grey Incidence Decision Model.

Jing Quan, Bo Zeng, Dai Liu

Complex., 2018

2016

Practical multispectral lighting reproduction.

Chloe LeGendre, Xueming Yu, Dai Liu, Jay Busch, Andrew Jones, Sumanta N. Pattanaik, Paul E. Debevec

ACM Trans. Graph., 2016