Papers
Pursuit-Evasion Without Regret, with an Application to Trading
Lili Dworkin, Michael Kearns, Yuriy Nevmyvaka
Putting MRFs on a Tensor Train
Alexander Novikov, Anton Rodomanov, Anton Osokin et al.
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Jiyan Yang, Vikas Sindhwani, Haim Avron et al.
Randomized Nonlinear Component Analysis
David Lopez-Paz, Suvrit Sra, Alex Smola et al.
Rank-One Matrix Pursuit for Matrix Completion
Zheng Wang, Ming-Jun Lai, Zhaosong Lu et al.
Rectangular Tiling Process
Masahiro Nakano, Katsuhiko Ishiguro, Akisato Kimura et al.
Recurrent Convolutional Neural Networks for Scene Labeling
Pedro Pinheiro, Ronan Collobert
Reducing Dueling Bandits to Cardinal Bandits
Nir Ailon, Zohar Karnin, Thorsten Joachims
Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem
Masrour Zoghi, Shimon Whiteson, Remi Munos et al.
Riemannian Pursuit for Big Matrix Recovery
Mingkui Tan, Ivor W. Tsang, Li Wang et al.
Robust and Efficient Kernel Hyperparameter Paths with Guarantees
Joachim Giesen, Soeren Laue, Patrick Wieschollek
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization
Hua Wang, Feiping Nie, Heng Huang
Robust Inverse Covariance Estimation under Noisy Measurements
Jun-Kun Wang, Shou-de Lin
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification
Junfeng Wen, Chun-Nam Yu, Russell Greiner
Robust Principal Component Analysis with Complex Noise
Qian Zhao, Deyu Meng, Zongben Xu et al.
Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models
Shike Mei, Jun Zhu, Jerry Zhu
Saddle Points and Accelerated Perceptron Algorithms
Adams Wei Yu, Fatma Kilinc-Karzan, Jaime Carbonell
Safe Screening with Variational Inequalities and Its Application to Lasso
Jun Liu, Zheng Zhao, Jie Wang et al.
Sample-based approximate regularization
Philip Bachman, Amir-Massoud Farahmand, Doina Precup
Sample Efficient Reinforcement Learning with Gaussian Processes
Robert Grande, Thomas Walsh, Jonathan How
Scalable and Robust Bayesian Inference via the Median Posterior
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin et al.
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo et al.
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications
Sebastien Bratieres, Novi Quadrianto, Sebastian Nowozin et al.
Scalable Semidefinite Relaxation for Maximum A Posterior Estimation
Qixing Huang, Yuxin Chen, Leonidas Guibas
Scaling SVM and Least Absolute Deviations via Exact Data Reduction
Jie Wang, Peter Wonka, Jieping Ye