Tianyi Zhou
Tianyi Zhou
Assistant Professor of Computer Science, University of Maryland, College Park
Verified email at - Homepage
Cited by
Cited by
Disan: Directional self-attention network for rnn/cnn-free language understanding
T Shen, T Zhou, G Long, J Jiang, S Pan, C Zhang
AAAI 2018, arXiv preprint arXiv:1709.04696, 2017
Godec: Randomized low-rank & sparse matrix decomposition in noisy case
T Zhou, D Tao
International Conference on Machine Learning 3, 2, 2011
Fedproto: Federated prototype learning across heterogeneous clients
Y Tan, G Long, L Liu, T Zhou, Q Lu, J Jiang, C Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8432-8440, 2022
Rethinking 1d-cnn for time series classification: A stronger baseline
W Tang, G Long, L Liu, T Zhou, J Jiang, M Blumenstein
ICLR 2022, arXiv preprint arXiv:2002.10061, 1-7, 2020
Manifold elastic net: a unified framework for sparse dimension reduction
T Zhou, D Tao, X Wu
Data Mining and Knowledge Discovery 22 (3), 340-371, 2011
Structure-augmented text representation learning for efficient knowledge graph completion
B Wang, T Shen, G Long, T Zhou, Y Wang, Y Chang
Proceedings of the Web Conference 2021, 1737-1748, 2021
Bi-directional block self-attention for fast and memory-efficient sequence modeling
T Shen, T Zhou, G Long, J Jiang, C Zhang
ICLR 2018, 2018
Curriculum-guided hindsight experience replay
M Fang, T Zhou, Y Du, L Han, Z Zhang
NeurIPS 2019, 2019
Reinforced self-attention network: a hybrid of hard and soft attention for sequence modeling
T Shen, T Zhou, G Long, J Jiang, S Wang, C Zhang
arXiv preprint arXiv:1801.10296 (accepted by IJCAI 2018), 2018
Multi-center federated learning
M Xie, G Long, T Shen, T Zhou, X Wang, J Jiang, C Zhang
arXiv preprint arXiv:2005.01026, 2021
Federated learning from pre-trained models: A contrastive learning approach
Y Tan, G Long, J Ma, L Liu, T Zhou, J Jiang
Advances in Neural Information Processing Systems (NeurIPS 2022), arXiv …, 2022
Alpagasus: Training a better alpaca with fewer data
L Chen, S Li, J Yan, H Wang, K Gunaratna, V Yadav, Z Tang, V Srinivasan, ...
arXiv preprint arXiv:2307.08701, 2023
Robust curriculum learning: from clean label detection to noisy label self-correction
T Zhou, S Wang, J Bilmes
International Conference on Learning Representations, 2020
Learning to propagate for graph meta-learning
L Liu, T Zhou, G Long, J Jiang, C Zhang
NeurIPS 2019, arXiv preprint arXiv:1909.05024, 2019
HallusionBench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models
T Guan, F Liu, X Wu, R Xian, Z Li, X Liu, X Wang, L Chen, F Huang, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction
Y Li, G Long, T Shen, T Zhou, L Yao, H Huo, J Jiang
AAAI 2020, 2019
Trustllm: Trustworthiness in large language models
L Sun, Y Huang, H Wang, S Wu, Q Zhang, C Gao, Y Huang, W Lyu, ...
arXiv preprint arXiv:2401.05561, 2024
Diverse client selection for federated learning via submodular maximization
R Balakrishnan, T Li, T Zhou, N Himayat, V Smith, J Bilmes
International Conference on Learning Representations, 2022
Curriculum Learning by Dynamic Instance Hardness
T Zhou, S Wang, JA Bilmes
NeurIPS 2020, 2020
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph
L Liu, T Zhou, G Long, J Jiang, L Yao, C Zhang
IJCAI 2019, 2019
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