Lu Liu

According to our database, Lu Liu authored at least 16 papers between 2019 and 2022.

Collaborative distances:

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

2022

Many-Class Few-Shot Learning on Multi-Granularity Class Hierarchy.

Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

IEEE Trans. Knowl. Data Eng., 2022

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size.

Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Federated Learning from Pre-Trained Models: A Contrastive Learning Approach.

Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Omni-Scale CNNs: a simple and effective kernel size configuration for time series classification.

Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Michael Blumenstein, Jing Jiang

Proceedings of the Tenth International Conference on Learning Representations, 2022

FedProto: Federated Prototype Learning across Heterogeneous Clients.

Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Episodic memory governs choices: An RNN-based reinforcement learning model for decision-making task.

Xiaohan Zhang, Lu Liu, Guodong Long, Jing Jiang, Shenquan Liu

Neural Networks, 2021

Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision.

Bo Li, Xinyang Jiang, Donglin Bai, Yuge Zhang, Ningxin Zheng, Xuanyi Dong, Lu Liu, Yuqing Yang, Dongsheng Li

CoRR, 2021

FedProto: Federated Prototype Learning over Heterogeneous Devices.

Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang

CoRR, 2021

Recognizing Vector Graphics without Rasterization.

Xinyang Jiang, Lu Liu, Caihua Shan, Yifei Shen, Xuanyi Dong, Dongsheng Li

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Isometric Propagation Network for Generalized Zero-shot Learning.

Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang

Proceedings of the 9th International Conference on Learning Representations, 2021

A Universal Representation Transformer Layer for Few-Shot Image Classification.

Lu Liu, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Rethinking 1D-CNN for Time Series Classification: A Stronger Baseline.

Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang, Michael Blumenstein

CoRR, 2020

Interpretable Time-series Classification on Few-shot Samples.

Wensi Tang, Lu Liu, Guodong Long

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Attribute Propagation Network for Graph Zero-Shot Learning.

Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Learning to Propagate for Graph Meta-Learning.

Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph.

Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019