Lin Lin

According to our database, Lin Lin authored at least 19 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2023

Multi-view clustering by CPS-merge analysis with application to multimodal single-cell data.

Lixiang Zhang, Lin Lin, Jia Li

PLoS Comput. Biol., 2023

2022

Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models.

Beomseok Seo, Lin Lin, Jia Li

J. Comput. Graph. Stat., 2022

Variational Interpretable Learning from Multi-view Data.

Lin Qiu, Lynn Lin, Vernon M. Chinchilli

CoRR, 2022

Probabilistic Model Incorporating Auxiliary Covariates to Control FDR.

Lin Qiu, Nils Murrugarra-Llerena, Vítor Silva, Lin Lin, Vernon M. Chinchilli

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Interpretable Representation Learning from Temporal Multi-view Data.

Lin Qiu, Vernon M. Chinchilli, Lin Lin

Proceedings of the Asian Conference on Machine Learning, 2022

2021

NeurT-FDR: Controlling FDR by Incorporating Feature Hierarchy.

Lin Qiu, Nils Murrugarra-Llerena, Vítor Silva, Lin Lin, Vernon M. Chinchilli

CoRR, 2021

Optimal Transport With Relaxed Marginal Constraints.

Jia Li, Lin Lin

IEEE Access, 2021

2020

Deep Latent Variable Model for Longitudinal Group Factor Analysis.

Lin Qiu, Vernon M. Chinchilli, Lin Lin

CoRR, 2020

CPS analysis: self-contained validation of biomedical data clustering.

Lixiang Zhang, Lin Lin, Jia Li

Bioinform., 2020

2019

Optimal transport, mean partition, and uncertainty assessment in cluster analysis.

Jia Li, Beomseok Seo, Lin Lin

Stat. Anal. Data Min., 2019

A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations.

Weiling Li, Lin Lin, Raunaq Malhotra, Lei Yang, Raj Acharya, Mary Poss

PLoS Comput. Biol., 2019

Bayesian multidimensional scaling procedure with variable selection.

Lin Lin, Duncan K. H. Fong

Comput. Stat. Data Anal., 2019

2018

Explaining Deep Learning Models - A Bayesian Non-parametric Approach.

Wenbo Guo, Sui Huang, Yunzhe Tao, Xinyu Xing, Lin Lin

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Defending Against Adversarial Samples Without Security through Obscurity.

Wenbo Guo, Qinglong Wang, Kaixuan Zhang, Alexander G. Ororbia II, Sui Huang, Xue Liu, C. Lee Giles, Lin Lin, Xinyu Xing

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Clustering with Hidden Markov Model on Variable Blocks.

Lin Lin, Jia Li

J. Mach. Learn. Res., 2017

Towards Interrogating Discriminative Machine Learning Models.

Wenbo Guo, Kaixuan Zhang, Lin Lin, Sui Huang, Xinyu Xing

CoRR, 2017

2016

Using Non-invertible Data Transformations to Build Adversary-Resistant Deep Neural Networks.

Qinglong Wang, Wenbo Guo, Alexander G. Ororbia II, Xinyu Xing, Lin Lin, C. Lee Giles, Xue Liu, Peng Liu, Gang Xiong

CoRR, 2016

From Physical to Cyber: Escalating Protection for Personalized Auto Insurance.

Le Guan, Jun Xu, Shuai Wang, Xinyu Xing, Lin Lin, Heqing Huang, Peng Liu, Wenke Lee

Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems, SenSys 2016, 2016

2013

Hierarchical Modeling for Rare Event Detection and Cell Subset Alignment across Flow Cytometry Samples.

Andrew Cron, Cécile Gouttefangeas, Jacob Frelinger, Lin Lin, Satwinder K. Singh, Cedrik M. Britten, Marij J. P. Welters, Sjoerd H. van der Burg, Mike West, Cliburn Chan

PLoS Comput. Biol., 2013