- Avanti Athreya, Zachary Lubberts, Carey E. Priebe, Youngser Park, Minh Tang, Vince Lyzinski, Michael J. Kane, Bryan Lewis. Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference. J. Comput. Graph. Stat., 32(1):145-156, January 2023.
- Charles A. Pehlivanian, Daniel B. Neill. Efficient Optimization of Partition Scan Statistics via the Consecutive Partitions Property. J. Comput. Graph. Stat., 32(2):712-729, April 2023.
- Yiqun T. Chen, Sean Jewell, Daniela M. Witten. More Powerful Selective Inference for the Graph Fused Lasso. J. Comput. Graph. Stat., 32(2):577-587, April 2023.
- Kan Chen, Siyu Heng, Qi Long, Bo Zhang. Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies. J. Comput. Graph. Stat., 32(2):528-538, April 2023.
- Aramayis Dallakyan, Mohsen Pourahmadi. Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series. J. Comput. Graph. Stat., 32(1):157-170, January 2023.
- Jingfei Zhang, Will Wei Sun, Lexin Li. Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies. J. Comput. Graph. Stat., 32(1):252-262, January 2023.
- Erjia Cui, Ruonan Li, Ciprian M. Crainiceanu, Luo Xiao. Fast Multilevel Functional Principal Component Analysis. J. Comput. Graph. Stat., 32(2):366-377, April 2023.
- Zhenyu Wei, Thomas C. M. Lee. High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference. J. Comput. Graph. Stat., 32(1):226-240, January 2023.
- Daniel Schalk, Bernd Bischl, David RĂ¼gamer. Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization. J. Comput. Graph. Stat., 32(2):631-641, April 2023.
- Matthys Lucas Steyn, Tertius de Wet, Bernard De Baets, Stijn Luca. A Nearest Neighbor Open-Set Classifier based on Excesses of Distance Ratios. J. Comput. Graph. Stat., 32(1):319-328, January 2023.