Articles

1. The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks. --Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs
2. Online Detection of Changes in Moment--Based Projections: When to Retrain Deep Learners or Update Portfolios?. --Ansgar Steland
3. Efficient frequent directions algorithms for approximate decomposition of matrices and higher-order tensors. --Maolin Che, Yimin Wei, Hong Yan
4. Identifying Weight-Variant Latent Causal Models. --Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
5. Classification Under Local Differential Privacy with Model Reversal and Model Averaging. --Caihong Qin, Yang Bai
6. Stochastic Gradient Methods: Bias, Stability and Generalization. --Shuang Zeng, Yunwen Lei
7. Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation. --Bohan Wu, David M. Blei
8. Skwdro: a library for Wasserstein distributionally robust machine learning. --Vincent Florian, Waïss Azizian, Franck Iutzeler, Jérôme Malick
9. Guaranteed Nonconvex Low-Rank Tensor Estimation via Scaled Gradient Descent. --Tong Wu
10. A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation. --Chenghao Li, Yuanyuan Lin; 11. Nonlocal Techniques for the Analysis of Deep ReLU Neural Network Approximations. --Cornelia Schneider, Mario Ullrich, Jan Vybíral
12. Nonlinear function-on-function regression by RKHS. --Peijun Sang, Bing Li
13. UQLM: A Python Package for Uncertainty Quantification in Large Language Models. --Dylan Bouchard, Mohit Singh Chauhan, David Skarbrevik, Ho-Kyeong Ra, Viren Bajaj, Zeya Ahmad
14. A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design. --Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan
15. Error Analysis for Deep ReLU Feedforward Density-Ratio Estimation with Bregman Divergence. --Siming Zheng, Guohao Shen, Yuanyuan Lin, Jian Huang
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