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2020 – today
- 2024
[c14]Yifeng Luo
, Yupeng Li, Dacheng Wen, Liang Lan:
Message Injection Attack on Rumor Detection under the Black-Box Evasion Setting Using Large Language Model. WWW 2024: 4512-4522- 2023
- [j12]Yu Geng, Liang Lan, William K. Cheung:
Toward Memory-Efficient and Interpretable Factorization Machines via Data and Model Binarization. IEEE Access 11: 128633-128643 (2023) - [j11]Liang Lan, Tao Huang, Yupeng Li, Yunya Song:
A Survey of Cross-Lingual Text Classification and Its Applications on Fake News Detection. World Sci. Annu. Rev. Artif. Intell. 1: 2350003:1-2350003:28 (2023) - 2022
- [c13]Guanrong Li, Ziwei Wang, Minzhu Zhao, Yunya Song, Liang Lan:
Sentiment Analysis of Political Posts on Hong Kong Local Forums Using Fine-Tuned mBERT. IEEE Big Data 2022: 6763-6765 - [c12]Zi Hen Lin, Ziwei Wang, Minzhu Zhao, Yunya Song, Liang Lan:
An AI-based System to Assist Human Fact-Checkers for Labeling Cantonese Fake News on Social Media. IEEE Big Data 2022: 6766-6768 - 2021
- [j10]Jiaxing Chen, Chinwang Cheong, Liang Lan, Xin Zhou, Jiming Liu, Aiping Lyu, William K. Cheung, Lu Zhang:
DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data. Briefings Bioinform. 22(6) (2021) - [c11]Weichao Lan, Liang Lan:
Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters. AAAI 2021: 8235-8242 - [c10]Zijian Lei, Liang Lan:
Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients. AAAI 2021: 8316-8323 - [c9]Ziwei Wang, Minzhu Zhao, Yu Chen, Yunya Song, Liang Lan:
A Study of Cantonese Covid-19 Fake News Detection on Social Media. IEEE BigData 2021: 6052-6054 - [i6]Yu Geng, Liang Lan:
Memory-Efficient Factorization Machines via Binarizing both Data and Model Coefficients. CoRR abs/2108.07421 (2021) - 2020
- [c8]Zijian Lei, Liang Lan:
Improved Subsampled Randomized Hadamard Transform for Linear SVM. AAAI 2020: 4519-4526 - [i5]Zijian Lei, Liang Lan:
Improved Subsampled Randomized Hadamard Transform for Linear SVM. CoRR abs/2002.01628 (2020) - [i4]Zijian Lei, Liang Lan:
Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients. CoRR abs/2010.02577 (2020) - [i3]Weichao Lan, Liang Lan:
Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters. CoRR abs/2010.02778 (2020) - [i2]Yuhan Wang, Zijian Lei, Liang Lan:
Effective and Sparse Count-Sketch via k-means clustering. CoRR abs/2011.12046 (2020)
2010 – 2019
- 2019
- [j9]Liang Lan, Zhuang Wang, Shandian Zhe, Wei Cheng, Jun Wang, Kai Zhang:
Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach. IEEE Trans. Neural Networks Learn. Syst. 30(2): 369-378 (2019) - [c7]Liang Lan, Yu Geng:
Accurate and Interpretable Factorization Machines. AAAI 2019: 4139-4146 - 2017
- [j8]Liang Lan, Kai Zhang, Hancheng Ge, Wei Cheng, Jun Liu, Andreas Rauber, Xiaoli Li, Jun Wang, Hongyuan Zha:
Low-rank decomposition meets kernel learning: A generalized Nyström method. Artif. Intell. 250: 1-15 (2017) - 2015
- [j7]Tao Huang, Liang Lan, Xuexian Fang, Peng An, Junxia Min, FuDi Wang:
Promises and Challenges of Big Data Computing in Health Sciences. Big Data Res. 2(1): 2-11 (2015) - [j6]Kai Zhang, Liang Lan, James T. Kwok, Slobodan Vucetic, Bahram Parvin:
Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 26(3): 444-457 (2015) - 2014
- [j5]Kai Zhang, Qiaojun Wang, Liang Lan, Yu Sun, Ivan Marsic:
Sparse semi-supervised learning on low-rank kernel. Neurocomputing 129: 265-272 (2014) - [c6]Liang Lan, Vuk Malbasa, Slobodan Vucetic:
Spatial Scan for Disease Mapping on a Mobile Population. AAAI 2014: 431-437 - [c5]Shiming Zhang, Yin Yang, Wei Fan, Liang Lan, Mingxuan Yuan:
OceanRT: real-time analytics over large temporal data. SIGMOD Conference 2014: 1099-1102 - 2013
- [j4]Liang Lan, Nemanja Djuric, Yuhong Guo, Slobodan Vucetic:
MS-kNN: protein function prediction by integrating multiple data sources. BMC Bioinform. 14(S-3): S8 (2013) - [j3]Nemanja Djuric, Liang Lan, Slobodan Vucetic, Zhuang Wang:
BudgetedSVM: a toolbox for scalable SVM approximations. J. Mach. Learn. Res. 14(1): 3813-3817 (2013) - 2012
- [j2]Zhuang Wang, Liang Lan, Slobodan Vucetic:
Mixture Model for Multiple Instance Regression and Applications in Remote Sensing. IEEE Trans. Geosci. Remote. Sens. 50(6): 2226-2237 (2012) - [c4]Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber:
Improved Nystrom Low-rank Decomposition with Priors. ICML 2012 - [c3]Kai Zhang, Liang Lan, Zhuang Wang, Fabian Moerchen:
Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach. AISTATS 2012: 1425-1434 - [i1]Kai Zhang, Liang Lan, Jun Liu, Andreas Rauber, Fabian Moerchen:
Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method. CoRR abs/1206.4619 (2012) - 2011
- [j1]Liang Lan, Slobodan Vucetic:
Improving accuracy of microarray classification by a simple multi-task feature selection filter. Int. J. Data Min. Bioinform. 5(2): 189-208 (2011) - [c2]Liang Lan, Haidong Shi, Zhuang Wang, Slobodan Vucetic:
Active Learning Based on Parzen Window. Active Learning and Experimental Design @ AISTATS 2011: 99-112
2000 – 2009
- 2009
- [c1]Liang Lan, Slobodan Vucetic:
A Multi-task Feature Selection Filter for Microarray Classification. BIBM 2009: 160-165
Coauthor Index
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