Research
I have great interest in statistical computing, deep learning, exact inference methods, large-scale data analysis, and data visualization.
Work in Progress
- Qiu, Y., Lei, J., and Roeder, K., Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning. Under review.
- Qiu, Y. and Zhang, L., Exact Tests for the Multivariate Behrens–Fisher Problem. To be submitted.
Publication
- Qiu, Y. and Wang, X., ALMOND: Adaptive Latent Modeling and Optimization via Neural Networks and Langevin Diffusion. Accepted by Journal of the American Statistical Association, 2019+.
- Qiu, Y., Zhang, L., and Wang, X., Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models. Accepted by International Conference on Learning Representations (ICLR 2020), 2019+.
- Qiu, Y. and Wang, X., Stochastic Approximate Gradient Descent via the Langevin Algorithm. Accepted by AAAI Conference on Artificial Intelligence (AAAI 2020), 2019+.
- 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.
- Qiu, Y., Zhang, L., and Liu, C., Exact and Efficient Inference for Partial Bayes Problems. Electronic Journal of Statistics, 2018.
- 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.
- Abraham, G., Qiu, Y., and Inouye, M., FlashPCA2: Principal Component Analysis of Biobank-scale Genotype Datasets. Bioinformatics, 2017.
- Qiu, Y., Wang, X. et al., Web Usage Cluster Analysis Based on Prediction Strength. International Conference on Instrumentation, Measurement, Circuits and Systems, 2011.
Invited Conference Talks
- 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
- 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.