Papers
Simultaneous Change Point Inference and Structure Recovery for High Dimensional Gaussian Graphical Models
Bin Liu, Xinsheng Zhang, Yufeng Liu
Single and Multiple Change-Point Detection with Differential Privacy
Wanrong Zhang, Sara Krehbiel, Rui Tuo et al.
sklvq: Scikit Learning Vector Quantization
Rick van Veen, Michael Biehl, Gert-Jan de Vries
Soft Tensor Regression
Georgia Papadogeorgou, Zhengwu Zhang, David B. Dunson
Some Theoretical Insights into Wasserstein GANs
Gérard Biau, Maxime Sangnier, Ugo Tanielian
Sparse and Smooth Signal Estimation: Convexification of L0-Formulations
Alper Atamturk, Andres Gomez, Shaoning Han
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
Kyriakos Axiotis, Maxim Sviridenko
Sparse Popularity Adjusted Stochastic Block Model
Majid Noroozi, Marianna Pensky, Ramchandra Rimal
Sparse Tensor Additive Regression
Botao Hao, Boxiang Wang, Pengyuan Wang et al.
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler, Dan Alistarh, Tal Ben-Nun et al.
Stable-Baselines3: Reliable Reinforcement Learning Implementations
Antonin Raffin, Ashley Hill, Adam Gleave et al.
Statistical guarantees for local graph clustering
Wooseok Ha, Kimon Fountoulakis, Michael W. Mahoney
Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs
Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani
Statistically and Computationally Efficient Change Point Localization in Regression Settings
Daren Wang, Zifeng Zhao, Kevin Z. Lin et al.
Statistical Query Lower Bounds for Tensor PCA
Rishabh Dudeja, Daniel Hsu
Stochastic Online Optimization using Kalman Recursion
Joseph de Vilmarest, Olivier Wintenberger
Stochastic Proximal AUC Maximization
Yunwen Lei, Yiming Ying
Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization
Michael R. Metel, Akiko Takeda
Strong Consistency, Graph Laplacians, and the Stochastic Block Model
Shaofeng Deng, Shuyang Ling, Thomas Strohmer
Structure Learning of Undirected Graphical Models for Count Data
Nguyen Thi Kim Hue, Monica Chiogna
Subspace Clustering through Sub-Clusters
Weiwei Li, Jan Hannig, Sayan Mukherjee
TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
Paweł Rościszewski, Michał Martyniak, Filip Schodowski
Testing Conditional Independence via Quantile Regression Based Partial Copulas
Lasse Petersen, Niels Richard Hansen
The Decoupled Extended Kalman Filter for Dynamic Exponential-Family Factorization Models
Carlos A. Gomez-Uribe, Brian Karrer