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Lingjing Kong 0001

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affiliation: EPFL, Machine Learning and Optimization Laboratory, Switzerland
affiliation (former): University of Edinburgh, LiFi R&D Centre, UK

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2020 – today

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2021
[c6]
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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]
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Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
Consensus Control for Decentralized Deep Learning. ICML 2021: 5686-5696
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Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich:
Consensus Control for Decentralized Deep Learning. CoRR abs/2102.04828 (2021)
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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
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Fei Mi, Lingjing Kong, Tao Lin, Kaicheng Yu, Boi Faltings:
Generalized Class Incremental Learning. CVPR Workshops 2020: 970-974
[c3]
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Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Extrapolation for Large-batch Training in Deep Learning. ICML 2020: 6094-6104
[c2]
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Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Ensemble Distillation for Robust Model Fusion in Federated Learning. NeurIPS 2020
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  - journals/corr/abs-2006-05720
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Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi:
Extrapolation for Large-batch Training in Deep Learning. CoRR abs/2006.05720 (2020)
[i1]
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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

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2018
[c1]
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Lingjing Kong, Cheng Chen, Yunlu Wang, Harald Haas:
Power Consumption Evaluation in High Speed Visible Light Communication Systems. GLOBECOM 2018: 1-6

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