Papers
Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets
Jie Wang, Zhanqiu Zhang, Jieping Ye
Unsupervised Basis Function Adaptation for Reinforcement Learning
Edward Barker, Charl Ras
Unsupervised Evaluation and Weighted Aggregation of Ranked Classification Predictions
Mehmet Eren Ahsen, Robert M Vogel, Gustavo A Stolovitzky
Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots
Akshara Rai, Rika Antonova, Franziska Meier et al.
Utilizing Second Order Information in Minibatch Stochastic Variance Reduced Proximal Iterations
Jialei Wang, Tong Zhang
Variance-based Regularization with Convex Objectives
John Duchi, Hongseok Namkoong
Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay, Yair Weiss
Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization
Tomoyuki Obuchi, Yoshiyuki Kabashima
A Cluster Elastic Net for Multivariate Regression
Bradley S. Price, Ben Sherwood
A Constructive Approach to $L_0$ Penalized Regression
Jian Huang, Yuling Jiao, Yanyan Liu et al.
Active Nearest-Neighbor Learning in Metric Spaces
Aryeh Kontorovich, Sivan Sabato, Ruth Urner
A Direct Approach for Sparse Quadratic Discriminant Analysis
Binyan Jiang, Xiangyu Wang, Chenlei Leng
A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference
Ahmed M. Alaa, Mihaela van der Schaar
An $\ell_{\infty}$ Eigenvector Perturbation Bound and Its Application
Jianqing Fan, Weichen Wang, Yiqiao Zhong
An efficient distributed learning algorithm based on effective local functional approximations
Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi et al.
A New and Flexible Approach to the Analysis of Paired Comparison Data
Ivo F. D. Oliveira, Nir Ailon, Ori Davidov
A Note on Quickly Sampling a Sparse Matrix with Low Rank Expectation
Karl Rohe, Jun Tao, Xintian Han et al.
A Robust Learning Approach for Regression Models Based on Distributionally Robust Optimization
Ruidi Chen, Ioannis Ch. Paschalidis
A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms
Bhavya Kailkhura, Jayaraman J. Thiagarajan, Charvi Rastogi et al.
A Study of the Classification of Low-Dimensional Data with Supervised Manifold Learning
Elif Vural, Christine Guillemot
A Theory of Learning with Corrupted Labels
Brendan van Rooyen, Robert C. Williamson
A Tight Bound of Hard Thresholding
Jie Shen, Ping Li