Papers
Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks
Peter L. Bartlett, Nick Harvey, Christopher Liaw et al.
Multi-scale Online Learning: Theory and Applications to Online Auctions and Pricing
Sébastien Bubeck, Nikhil R. Devanur, Zhiyi Huang et al.
The Sup-norm Perturbation of HOSVD and Low Rank Tensor Denoising
Dong Xia, Fan Zhou
Robust Estimation of Derivatives Using Locally Weighted Least Absolute Deviation Regression
WenWu Wang, Ping Yu, Lu Lin et al.
Kernel Approximation Methods for Speech Recognition
Avner May, Alireza Bagheri Garakani, Zhiyun Lu et al.
The Common-directions Method for Regularized Empirical Risk Minimization
Po-Wei Wang, Ching-pei Lee, Chih-Jen Lin
Multi-class Heterogeneous Domain Adaptation
Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan et al.
Neural Architecture Search: A Survey
Thomas Elsken, Jan Hendrik Metzen, Frank Hutter
Deep Reinforcement Learning for Swarm Systems
Maximilian Hüttenrauch, Adrian Šošić, Gerhard Neumann
Tunability: Importance of Hyperparameters of Machine Learning Algorithms
Philipp Probst, Anne-Laure Boulesteix, Bernd Bischl
Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems
Sondre Glimsdal, Ole-Christoffer Granmo
Bayesian Combination of Probabilistic Classifiers using Multivariate Normal Mixtures
Gregor Pirš, Erik Štrumbelj
No-Regret Bayesian Optimization with Unknown Hyperparameters
Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots
Akshara Rai, Rika Antonova, Franziska Meier et al.
Efficient augmentation and relaxation learning for individualized treatment rules using observational data
Ying-Qi Zhao, Eric B. Laber, Yang Ning et al.
Analysis of spectral clustering algorithms for community detection: the general bipartite setting
Zhixin Zhou, Arash A.Amini
Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping
Shao-Bo Lin, Yunwen Lei, Ding-Xuan Zhou
Robust Frequent Directions with Application in Online Learning
Luo Luo, Cheng Chen, Zhihua Zhang et al.
Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python
Jason Ge, Xingguo Li, Haoming Jiang et al.
DSCOVR: Randomized Primal-Dual Block Coordinate Algorithms for Asynchronous Distributed Optimization
Lin Xiao, Adams Wei Yu, Qihang Lin et al.
Utilizing Second Order Information in Minibatch Stochastic Variance Reduced Proximal Iterations
Jialei Wang, Tong Zhang
Decontamination of Mutual Contamination Models
Julian Katz-Samuels, Gilles Blanchard, Clayton Scott
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations
Qianxiao Li, Cheng Tai, Weinan E
A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication
Miles E. Lopes, Shusen Wang, Michael W. Mahoney