Liang Lan

Orcid: 0000-0002-0427-977X

According to our database1, Liang Lan authored at least 28 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
A Survey of Cross-Lingual Text Classification and Its Applications on Fake News Detection.
World Sci. Annu. Rev. Artif. Intell., 2023

Toward Memory-Efficient and Interpretable Factorization Machines via Data and Model Binarization.
IEEE Access, 2023

2022
An AI-based System to Assist Human Fact-Checkers for Labeling Cantonese Fake News on Social Media.
Proceedings of the IEEE International Conference on Big Data, 2022

Sentiment Analysis of Political Posts on Hong Kong Local Forums Using Fine-Tuned mBERT.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Memory-Efficient Factorization Machines via Binarizing both Data and Model Coefficients.
CoRR, 2021

DeepDRIM: a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data.
Briefings Bioinform., 2021

A Study of Cantonese Covid-19 Fake News Detection on Social Media.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Effective and Sparse Count-Sketch via k-means clustering.
CoRR, 2020

Improved Subsampled Randomized Hadamard Transform for Linear SVM.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Scaling Up Kernel SVM on Limited Resources: A Low-Rank Linearization Approach.
IEEE Trans. Neural Networks Learn. Syst., 2019

Accurate and Interpretable Factorization Machines.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017
Low-rank decomposition meets kernel learning: A generalized Nyström method.
Artif. Intell., 2017

2015
Scaling Up Graph-Based Semisupervised Learning via Prototype Vector Machines.
IEEE Trans. Neural Networks Learn. Syst., 2015

Promises and Challenges of Big Data Computing in Health Sciences.
Big Data Res., 2015

2014
Sparse semi-supervised learning on low-rank kernel.
Neurocomputing, 2014

OceanRT: real-time analytics over large temporal data.
Proceedings of the International Conference on Management of Data, 2014

Spatial Scan for Disease Mapping on a Mobile Population.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
BudgetedSVM: a toolbox for scalable SVM approximations.
J. Mach. Learn. Res., 2013

MS-kNN: protein function prediction by integrating multiple data sources.
BMC Bioinform., 2013

2012
Mixture Model for Multiple Instance Regression and Applications in Remote Sensing.
IEEE Trans. Geosci. Remote. Sens., 2012

Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
CoRR, 2012

Improved Nystrom Low-rank Decomposition with Priors.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Active Learning Based on Parzen Window.
Proceedings of the Active Learning and Experimental Design workshop, 2011

Improving accuracy of microarray classification by a simple multi-task feature selection filter.
Int. J. Data Min. Bioinform., 2011

2009
A Multi-task Feature Selection Filter for Microarray Classification.
Proceedings of the 2009 IEEE International Conference on Bioinformatics and Biomedicine, 2009


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