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ORCIDLingjing Kong 0001
Person information
- affiliation: EPFL, Machine Learning and Optimization Laboratory, Switzerland
- affiliation (former): University of Edinburgh, LiFi R&D Centre, UK
Other persons with the same name
- Lingjing Kong — disambiguation page
- Lingjing Kong 0002 — Shenzhen Institute of Information Technology, Department of Computer, Shenzhen, China (and 1 more)
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2020 – today
- 2021
[c6]Fei Mi, Wanhao Zhou, Lingjing Kong, Fengyu Cai, Minlie Huang, Boi Faltings:
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems. EMNLP (1) 2021: 1887-1898- [c5]Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
Consensus Control for Decentralized Deep Learning. ICML 2021: 5686-5696 - [i4]Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
Consensus Control for Decentralized Deep Learning. CoRR abs/2102.04828 (2021) - [i3]Fei Mi, Wanhao Zhou, Fengyu Cai, Lingjing Kong, Minlie Huang, Boi Faltings:
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems. CoRR abs/2108.12589 (2021) - 2020
- [c4]Fei Mi, Lingjing Kong, Tao Lin, Kaicheng Yu, Boi Faltings:
Generalized Class Incremental Learning. CVPR Workshops 2020: 970-974 - [c3]Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Extrapolation for Large-batch Training in Deep Learning. ICML 2020: 6094-6104 - [c2]Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Ensemble Distillation for Robust Model Fusion in Federated Learning. NeurIPS 2020 - [i2]Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Extrapolation for Large-batch Training in Deep Learning. CoRR abs/2006.05720 (2020) - [i1]Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Ensemble Distillation for Robust Model Fusion in Federated Learning. CoRR abs/2006.07242 (2020)
2010 – 2019
- 2018
- [c1]Lingjing Kong, Cheng Chen, Yunlu Wang, Harald Haas
:
Power Consumption Evaluation in High Speed Visible Light Communication Systems. GLOBECOM 2018: 1-6
Coauthor Index
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