Papers
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models
Botao Hao, Will Wei Sun, Yufeng Liu et al.
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang, Alex Gittens, Michael W. Mahoney
Sparse Concordance-assisted Learning for Optimal Treatment Decision
Shuhan Liang, Wenbin Lu, Rui Song et al.
Sparse Estimation in Ising Model via Penalized Monte Carlo Methods
Blazej Miasojedow, Wojciech Rejchel
Sparse Exchangeable Graphs and Their Limits via Graphon Processes
Christian Borgs, Jennifer T. Chayes, Henry Cohn et al.
Statistical Analysis and Parameter Selection for Mapper
Mathieu Carrière, Bertrand Michel, Steve Oudot
Statistical Inference on Random Dot Product Graphs: a Survey
Avanti Athreya, Donniell E. Fishkind, Minh Tang et al.
Steering Social Activity: A Stochastic Optimal Control Point Of View
Ali Zarezade, Abir De, Utkarsh Upadhyay et al.
Streaming kernel regression with provably adaptive mean, variance, and regularization
Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau
Submatrix localization via message passing
Bruce Hajek, Yihong Wu, Jiaming Xu
Surprising properties of dropout in deep networks
David P. Helmbold, Philip M. Long
The DFS Fused Lasso: Linear-Time Denoising over General Graphs
Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott et al.
The Implicit Bias of Gradient Descent on Separable Data
Daniel Soudry, Elad Hoffer, Mor Shpigel Nacson et al.
Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier
Alain Celisse, Tristan Mary-Huard
The Search Problem in Mixture Models
Avik Ray, Joe Neeman, Sujay Sanghavi et al.
The xyz algorithm for fast interaction search in high-dimensional data
Gian-Andrea Thanei, Nicolai Meinshausen, Rajen D. Shah
ThunderSVM: A Fast SVM Library on GPUs and CPUs
Zeyi Wen, Jiashuai Shi, Qinbin Li et al.
tick: a Python Library for Statistical Learning, with an emphasis on Hawkes Processes and Time-Dependent Models
Emmanuel Bacry, Martin Bompaire, Philip Deegan et al.
To Tune or Not to Tune the Number of Trees in Random Forest
Philipp Probst, Anne-Laure Boulesteix
Training Gaussian Mixture Models at Scale via Coresets
Mario Lucic, Matthew Faulkner, Andreas Krause et al.
Uncovering Causality from Multivariate Hawkes Integrated Cumulants
Massil Achab, Emmanuel Bacry, Stéphane Gaïffas et al.
Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems
Lyudmila Grigoryeva, Juan-Pablo Ortega
Using Side Information to Reliably Learn Low-Rank Matrices from Missing and Corrupted Observations
Kai-Yang Chiang, Inderjit S. Dhillon, Cho-Jui Hsieh
Variational Fourier Features for Gaussian Processes
James Hensman, Nicolas Durrande, Arno Solin