Papers
High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm
Wenlong Mou, Yi-An Ma, Martin J. Wainwright et al.
Histogram Transform Ensembles for Large-scale Regression
Hanyuan Hang, Zhouchen Lin, Xiaoyu Liu et al.
Hoeffding's Inequality for General Markov Chains and Its Applications to Statistical Learning
Jianqing Fan, Bai Jiang, Qiang Sun
Homogeneity Structure Learning in Large-scale Panel Data with Heavy-tailed Errors
Di Xiao, Yuan Ke, Runze Li
How to Gain on Power: Novel Conditional Independence Tests Based on Short Expansion of Conditional Mutual Information
Mariusz Kubkowski, Jan Mielniczuk, Paweł Teisseyre
How Well Generative Adversarial Networks Learn Distributions
Tengyuan Liang
Hyperparameter Optimization via Sequential Uniform Designs
Zebin Yang, Aijun Zhang
Implicit Langevin Algorithms for Sampling From Log-concave Densities
Liam Hodgkinson, Robert Salomone, Fred Roosta
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning
Charles H. Martin, Michael W. Mahoney
Improved Shrinkage Prediction under a Spiked Covariance Structure
Trambak Banerjee, Gourab Mukherjee, Debashis Paul
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program)
Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha et al.
Incorporating Unlabeled Data into Distributionally Robust Learning
Charlie Frogner, Sebastian Claici, Edward Chien et al.
Individual Fairness in Hindsight
Swati Gupta, Vijay Kamble
Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace
Jesús Arroyo, Avanti Athreya, Joshua Cape et al.
Inference for the Case Probability in High-dimensional Logistic Regression
Zijian Guo, Prabrisha Rakshit, Daniel S. Herman et al.
Inference In High-dimensional Single-Index Models Under Symmetric Designs
Hamid Eftekhari, Moulinath Banerjee, Ya'acov Ritov
Information criteria for non-normalized models
Takeru Matsuda, Masatoshi Uehara, Aapo Hyvarinen
Integrated Principal Components Analysis
Tiffany M. Tang, Genevera I. Allen
Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
Minjie Wang, Genevera I. Allen
Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints
Molei Liu, Yin Xia, Kelly Cho et al.
Interpretable Deep Generative Recommendation Models
Huafeng Liu, Liping Jing, Jingxuan Wen et al.
Is SGD a Bayesian sampler? Well, almost
Chris Mingard, Guillermo Valle-Pérez, Joar Skalse et al.
Kernel Operations on the GPU, with Autodiff, without Memory Overflows
Benjamin Charlier, Jean Feydy, Joan Alexis Glaunès et al.
Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data
Yikun Zhang, Yen-Chi Chen