Research
I have great interest in statistical computing, deep learning, exact inference methods, large-scale data analysis, and data visualization.
Publication
- Qiu, Y., Lei, J., and Roeder, K., Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning. Biometrika, 2022. Link Code
- Qiu, Y., Wang, J., Lei, J., and Roeder, K., Identification of Cell-type-specific Marker Genes from Co-expression Patterns in Tissue Samples. Bioinformatics, 2021. Link Code
- Qiu, Y. and Wang, X., ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion. Journal of the American Statistical Association, 2021. Link Code
- Qiu, Y. and Wang, X., Stochastic Approximate Gradient Descent via the Langevin Algorithm. AAAI Conference on Artificial Intelligence (AAAI 2020), 2020. Link PDF
- Qiu, Y., Zhang, L., and Wang, X., Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models. International Conference on Learning Representations (ICLR 2020), 2020. Link Code
- Lu, J.*, Qiu, Y.*, and Deng, A., A Note on Type S/M Errors in Hypothesis Testing. *Joint first authors. British Journal of Mathematical and Statistical Psychology, 2019. Link PDF
- Qiu, Y., Zhang, L., and Liu, C., Exact and Efficient Inference for Partial Bayes Problems. Electronic Journal of Statistics, 2018. Link
- Qiu, Y. and Wei, W., A Scalable Sequential Principal Component Analysis Algorithm (SeqPCA) with Application to User Access Control Analysis. IEEE International Conference on Big Data, 2017. Link
- Abraham, G., Qiu, Y., and Inouye, M., FlashPCA2: Principal Component Analysis of Biobank-scale Genotype Datasets. Bioinformatics, 2017. Link Code
- Qiu, Y., Wang, X. et al., Web Usage Cluster Analysis Based on Prediction Strength. International Conference on Instrumentation, Measurement, Circuits and Systems, 2011.
Invited Talks
- Efficient Multi-Modal Sampling via Tempered Distribution Flow
University of Missouri (online), 2021. - Prettier R Graphs and Documents with {showtext}+{prettydoc}
Cleveland R User Group (website), 2020. Slides - Gradient-based Sparse Principal Component Analysis
The 11th ICSA International Conference, 2019. Slides - Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion
The 36th Annual Quality and Productivity Research Conference, 2019. Slides - Exact Inference with Partially Specified Bayesian Models
2017 ICSA Applied Statistics Symposium, 2017. Slides - SupR: Multi-threaded R Environment
The 9th China-R Conference, 2016. Slides - Large-Scale SVD and Matrix Completion
The 7th China-R Conference, 2014.
Other Talks and Posters
- Unbiased Contrastive Divergence Algorithm for Training Energy-based Latent Variable Models
International Conference on Learning Representations (website), 2020. Slides Video - Stochastic Approximate Gradient Descent via the Underdamped Langevin Algorithm
AAAI Conference on Artificial Intelligence, 2020. Poster - Gradient-based Spase PCA with Extensions to Online Learning
Joint Statistical Meetings, 2019. - Stochastic Approximate Gradient Descent via the Underdamped Langevin Algorithm
SAMSI Deep Learning Workshop, 2019. Poster - Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion
Conference of the Science of Deep Learning, 2019. Poster - Exact and Efficient Inference for Partial Bayes Problems
Fifth Bayesian, Fiducial, and Frequentist (BFF5) Conference, 2018. Poster - Beyond Bayes: What We Can Do with a Partial Prior
Purdue Statistics Graduate Student Seminar, 2017. Slides - How To Make Your Code Faster
Purdue Statistics Graduate Student Seminar, 2016. Slides - Generalized p-Value for Two-Sample Functional Data Comparison
Joint Statistical Meetings, 2014. - Dynamic Document with knitr
Purdue Statistics Graduate Student Seminar, 2014. Slides
Book Translation
- Applied Predictive Modeling by Max Kuhn and Kjell Johnson.
- ggplot2: Elegant Graphics for Data Analysis by Hadley Wickham.
- The Art of R Programming by Norman Matloff.
- R Graphics Cookbook by Winston Chang.
