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Isometric Propagation Network for Generalized Zero-shot Learning


Feb 03, 2021
Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong, Chengqi Zhang

* Accepted by ICLR 2021 

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Free Lunch for Few-shot Learning: Distribution Calibration


Jan 16, 2021
Shuo Yang, Lu Liu, Min Xu

* The 9th International Conference on Learning Representations (ICLR 2021) 
* ICLR 2021 oral paper, code is available at https://github.com/ShuoYang-1998/ICLR2021-Oral_Distribution_Calibration 

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Attribute Propagation Network for Graph Zero-shot Learning


Sep 24, 2020
Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

* AAAI 2020 

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Improving Coreference Resolution by Leveraging Entity-Centric Features with Graph Neural Networks and Second-order Inference


Sep 10, 2020
Lu Liu, Zhenqiao Song, Xiaoqing Zheng


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NATS-Bench: Benchmarking NAS algorithms for Architecture Topology and Size


Sep 02, 2020
Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys

* An extended version of NAS-Bench-201 published in ICLR 2020. arXiv admin note: substantial text overlap with arXiv:2001.00326 

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


Jun 28, 2020
Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang


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A Universal Representation Transformer Layer for Few-Shot Image Classification


Jun 25, 2020
Lu Liu, William Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle


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Interpretable Time-series Classification on Few-shot Samples


Jun 03, 2020
Wensi Tang, Lu Liu, Guodong Long

* Accepted to IJCNN 2020 

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Low-shot Object Detection via Classification Refinement


May 06, 2020
Yiting Li, Yu Cheng, Lu Liu, Sichao Tian, Haiyue Zhu, Cheng Xiang, Prahlad Vadakkepat, Cheksing Teo, Tongheng Lee

* Submitted to NIPS2020 

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Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework


Apr 15, 2020
Jiehang Zeng, Lu Liu, Xiaoqing Zheng

* 7 pages, 1 figures 

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


Feb 24, 2020
Wensi Tang, Guodong Long, Lu Liu, Tianyi Zhou, Jing Jiang, Michael Blumenstein


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AutoML using Metadata Language Embeddings


Oct 08, 2019
Iddo Drori, Lu Liu, Yi Nian, Sharath C. Koorathota, Jie S. Li, Antonio Khalil Moretti, Juliana Freire, Madeleine Udell

* NeurIPS Workshop on Meta-Learning, 2019 

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Learning to Propagate for Graph Meta-Learning


Sep 11, 2019
Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

* Accepted to NeurIPS 2019 

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New Era of Deeplearning-Based Malware Intrusion Detection: The Malware Detection and Prediction Based On Deep Learning


Jul 19, 2019
Shuqiang Lu, Lingyun Ying, Wenjie Lin, Yu Wang, Meining Nie, Kaiwen Shen, Lu Liu, Haixin Duan


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


Jun 02, 2019
Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Lina Yao, Chengqi Zhang

* Accepted to IJCAI 2019, Code is publicly available at: https://github.com/liulu112601/PPN 

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Certainty-Driven Consistency Loss for Semi-supervised Learning


Jan 17, 2019
Yingting Li, Lu Liu, Robby T. Tan


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From Plots to Endings: A Reinforced Pointer Generator for Story Ending Generation


Jan 11, 2019
Yan Zhao, Lu Liu, Chunhua Liu, Ruoyao Yang, Dong Yu

* Natural Language Processing and Chinese Computing. NLPCC 2018. Lecture Notes in Computer Science, vol 11108. Springer, Cham 
* 12 pages, 1 figure, NLPCC 2018 

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Loss Guided Activation for Action Recognition in Still Images


Dec 11, 2018
Lu Liu, Robby T. Tan, Shaodi You

* Accepted to appear in ACCV 2018 

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Encoding Temporal Markov Dynamics in Graph for Visualizing and Mining Time Series


Aug 14, 2018
Lu Liu, Zhiguang Wang

* AAAI 2018 workshop 

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Representation Learning with Deconvolution for Multivariate Time Series Classification and Visualization


Nov 26, 2016
Zhiguang Wang, Wei Song, Lu Liu, Fan Zhang, Junxiao Xue, Yangdong Ye, Ming Fan, Mingliang Xu

* arXiv admin note: text overlap with arXiv:1505.04366 by other authors 

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