Papers
ORCA: A Matlab/Octave Toolbox for Ordinal Regression
Javier Sánchez-Monedero, Pedro A. Gutiérrez, María Pérez-Ortiz
Parsimonious Online Learning with Kernels via Sparse Projections in Function Space
Alec Koppel, Garrett Warnell, Ethan Stump et al.
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python
Jason Ge, Xingguo Li, Haoming Jiang et al.
Prediction Risk for the Horseshoe Regression
Anindya Bhadra, Jyotishka Datta, Yunfan Li et al.
Provably Accurate Double-Sparse Coding
Thanh V. Nguyen, Raymond K. W. Wong, Chinmay Hegde
Proximal Distance Algorithms: Theory and Practice
Kevin L. Keys, Hua Zhou, Kenneth Lange
PyOD: A Python Toolbox for Scalable Outlier Detection
Yue Zhao, Zain Nasrullah, Zheng Li
Pyro: Deep Universal Probabilistic Programming
Eli Bingham, Jonathan P. Chen, Martin Jankowiak et al.
Quantification Under Prior Probability Shift: the Ratio Estimator and its Extensions
Afonso Fernandes Vaz, Rafael Izbicki, Rafael Bassi Stern
Quantifying Uncertainty in Online Regression Forests
Theodore Vasiloudis, Gianmarco De Francisci Morales, Henrik Boström
Random Feature-based Online Multi-kernel Learning in Environments with Unknown Dynamics
Yanning Shen, Tianyi Chen, Georgios B. Giannakis
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning
Can Karakus, Yifan Sun, Suhas Diggavi et al.
Regularization via Mass Transportation
Soroosh Shafieezadeh-Abadeh, Daniel Kuhn, Peyman Mohajerin Esfahani
Relative Error Bound Analysis for Nuclear Norm Regularized Matrix Completion
Lijun Zhang, Tianbao Yang, Rong Jin et al.
Robust Estimation of Derivatives Using Locally Weighted Least Absolute Deviation Regression
WenWu Wang, Ping Yu, Lu Lin et al.
Robust Frequent Directions with Application in Online Learning
Luo Luo, Cheng Chen, Zhihua Zhang et al.
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise
Niklas Pfister, Sebastian Weichwald, Peter Bühlmann et al.
Scalable Approximations for Generalized Linear Problems
Murat Erdogdu, Mohsen Bayati, Lee H. Dicker
Scalable Interpretable Multi-Response Regression via SEED
Zemin Zheng, M. Taha Bahadori, Yan Liu et al.
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds
Shusen Wang, Alex Gittens, Michael W. Mahoney
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Bin Hong, Weizhong Zhang, Wei Liu et al.
scikit-multilearn: A Python library for Multi-Label Classification
Piotr Szymański, Tomasz Kajdanowicz
Semi-Analytic Resampling in Lasso
Tomoyuki Obuchi, Yoshiyuki Kabashima
Shared Subspace Models for Multi-Group Covariance Estimation
Alexander M. Franks, Peter Hoff
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery
Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei